Data & Analytics terms

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• Accessible VisualizationDesigning charts that people with disabilities, including color-vision deficiency and screen-reader users, can perceive and understand.Intermediate
• ACCOUNT_USAGE SchemaA schema in the shared SNOWFLAKE database with account-wide metadata and usage views such as QUERY_HISTORY, WAREHOUSE_METERING_HISTORY and ACCESS_HISTORY.Advanced
• Accumulating Snapshot Fact TableA fact table with one row per process instance, such as an order, that is updated as the process passes milestones.Advanced
• ACIDThe four properties of reliable transactions: Atomicity, Consistency, Isolation and Durability.Foundational
• Active Geo-ReplicationAn Azure SQL Database feature that maintains up to four readable secondary databases in the same or other regions using asynchronous replication.Advanced
• Active RelationshipThe single relationship between two Power BI tables that propagates filters by default; additional relationships are inactive.Intermediate
• Adaptive Query Execution (AQE)A Spark 3 feature that re-optimizes query plans at run time using actual shuffle statistics.Advanced
• Additive MeasureA fact that can be summed meaningfully across every dimension, such as sales amount or quantity.Intermediate
• Aggregate FunctionA function that computes one value from a set of rows, such as SUM, AVG, COUNT, MIN, MAX, STDDEV or LISTAGG.Foundational
• ALL FunctionA DAX function that returns all rows of a table or column, ignoring filters; inside CALCULATE it removes filters (like REMOVEFILTERS).Advanced
• ALTER TABLE StatementThe DDL statement that changes an existing table's structure, such as adding, dropping or modifying columns and constraints.Foundational
• Alternate KeyA candidate key that was not chosen as the primary key, usually enforced with a UNIQUE constraint.Intermediate
• Alternative Hypothesis (H1)The claim that there is an effect or difference, accepted when the null hypothesis is rejected.Foundational
• Always EncryptedA SQL Server and Azure SQL feature that encrypts sensitive columns on the client so the database engine and DBAs never see plaintext.Advanced
• Always On Availability Groups (AG)A SQL Server high-availability and disaster-recovery feature that replicates a group of databases to secondary replicas with automatic or manual failover.Advanced
• Amazon Data FirehoseA managed service (formerly Kinesis Data Firehose) that buffers and delivers streaming data to S3, Redshift, OpenSearch, Snowflake and more.Intermediate
• Amazon EMRAWS's managed big data platform for running Spark, Hive, Presto/Trino, Flink and other open-source frameworks on EC2, EKS or serverless.Intermediate
• Amazon Kinesis Data Streams (KDS)A managed AWS service for real-time streaming data, with shards that store ordered records for custom consumers to replay.Intermediate
• Amazon QuickSightAWS's serverless business intelligence service for dashboards, paginated reports and natural-language queries.Intermediate
• Analysis of Variance (ANOVA)A test of whether the means of three or more groups differ, by comparing between-group variance with within-group variance (the F-statistic).Intermediate
• ANSI SQLThe vendor-neutral SQL standard (ISO/IEC 9075) that defines core syntax and behavior that relational databases implement.Intermediate
• Anti JoinA join pattern that returns rows from one table that have no match in another.Intermediate
• Apache AirflowAn open-source platform for authoring, scheduling and monitoring workflows as Python-defined DAGs.Intermediate
• Apache AvroA row-based binary file format with an embedded JSON schema, well suited to streaming, write-heavy workloads and schema evolution.Intermediate
• Apache BeamAn open-source unified programming model for batch and streaming pipelines that run on runners such as Dataflow, Flink or Spark.Advanced
• Apache CassandraAn open-source, masterless, distributed wide-column database designed for high write throughput and multi-datacenter availability.Intermediate
• Apache HadoopAn open-source framework for distributed storage (HDFS) and batch processing (MapReduce, YARN) on clusters of commodity hardware.Foundational
• Apache HiveA data warehouse system on Hadoop that lets users query files with a SQL-like language (HiveQL) using schema on read.Intermediate
• Apache HudiAn open table format (Hadoop Upserts Deletes and Incrementals) focused on record-level upserts, deletes and incremental processing on data lakes.Advanced
• Apache IcebergAn open table format for huge analytic datasets that provides ACID commits, hidden partitioning, schema and partition evolution, and time travel.Advanced
• Apache KafkaA distributed event streaming platform that stores ordered, durable, replayable logs of records in partitioned topics.Intermediate
• Apache ORCOptimized Row Columnar: a columnar file format from the Hive ecosystem with lightweight indexes, compression and ACID support in Hive.Advanced
• Apache ParquetAn open-source columnar file format with efficient compression, encoding and predicate pushdown, widely used for analytics.Intermediate
• Apache SparkAn open-source distributed engine for large-scale data processing with in-memory computation and APIs for SQL, Python, Scala, Java and R.Foundational
• Append QueriesA Power Query operation that stacks rows from two or more queries with the same columns, like SQL UNION ALL.Foundational
• ARIMAAutoRegressive Integrated Moving Average: a forecasting model that combines autoregression, differencing (to reach stationarity) and moving-average error terms.Advanced
• Asynchronous ReplicationReplication in which the primary acknowledges writes immediately and ships changes to replicas afterward.Intermediate
• At-Least-Once DeliveryA delivery guarantee that every message is delivered one or more times, so duplicates are possible but loss is not.Advanced
• Atomic ValueA value that cannot be meaningfully divided further for the purposes of the data model.Foundational
• AtomicityThe ACID property that a transaction completes entirely or not at all.Foundational
• AttributeA property that describes an entity, implemented as a column in a table.Foundational
• Auto LoaderA Databricks feature (cloudFiles source) that incrementally and efficiently ingests new files from cloud storage, with schema inference and evolution.Intermediate
• Auto-Failover GroupAn Azure SQL Database and Managed Instance feature that replicates databases to another region and fails them over together behind stable listener endpoints.Advanced
• Auto-SuspendA setting that suspends a Snowflake warehouse after a set idle period so it stops using credits; auto-resume restarts it when queries arrive.Foundational
• Automatic TuningAn Azure SQL and SQL Server capability that automatically forces last-good plans and, in Azure SQL Database, can create or drop indexes.Advanced
• AWS GlueA serverless AWS data integration service for discovering, preparing and transforming data with Spark-based ETL jobs.Intermediate
• AWS Glue CrawlerA Glue component that scans data stores, infers schemas and partitions, and creates or updates tables in the Data Catalog.Intermediate
• AWS Glue Data CatalogA managed, Hive-compatible metadata repository of databases, tables and partitions used by Athena, EMR, Redshift Spectrum and Glue.Intermediate
• AWS Lake FormationAn AWS service that builds and centrally governs data lakes, with fine-grained permissions at database, table, column, row and cell level.Advanced
• Azure Data Factory (ADF)Azure's cloud ETL and data integration service for building pipelines of activities with 90+ connectors.Intermediate
• Azure Data Lake Storage Gen2 (ADLS Gen2)Azure Blob Storage with a hierarchical namespace enabled, providing directory semantics, POSIX-style ACLs and big data analytics performance.Intermediate
• Azure SQL Elastic PoolA shared pool of compute and storage resources for multiple Azure SQL databases with variable, unpredictable usage.Intermediate
• Azure SQL HyperscaleAn Azure SQL Database service tier with a distributed storage architecture that supports databases up to 128 TB, fast scaling and near-instant backups.Advanced
• Azure Stream Analytics (ASA)A serverless real-time analytics service that runs SQL-like queries over streams from Event Hubs, IoT Hub or Blob Storage.Advanced
• Azure Synapse AnalyticsAzure's analytics service combining dedicated and serverless SQL pools, Spark pools and pipelines; Microsoft now positions Fabric as its successor.Intermediate
• B-Tree IndexA balanced tree index that keeps keys sorted and supports equality, range and ORDER BY lookups in logarithmic time.Intermediate
• BackfillRunning a pipeline over historical periods to populate or correct past data.Intermediate
• BackgrounderThe Tableau Server process that runs scheduled and background jobs: extract refreshes, subscriptions, flows and alerts.Advanced
• Bar ChartA chart that compares values across categories using rectangular bars whose lengths are proportional to the values.Foundational
• BASEA NoSQL consistency model: Basically Available, Soft state, Eventually consistent, the counterpoint to ACID.Intermediate
• Batch ProcessingProcessing accumulated data in discrete scheduled jobs, such as hourly or nightly loads.Foundational
• Bayes' TheoremA rule for updating the probability of a hypothesis given evidence: P(A|B) = P(B|A) × P(A) / P(B).Intermediate
• BETWEEN OperatorA predicate that tests whether a value lies within an inclusive range: x BETWEEN a AND b means x >= a AND x <= b.Foundational
• Big DataDatasets too large, fast or varied for traditional single-server databases to store and process efficiently.Foundational
• Binomial DistributionThe distribution of the number of successes in n independent trials, each with the same success probability p.Intermediate
• BinsEqual-sized intervals created from a continuous measure, used to build histograms.Intermediate
• Bitmap IndexAn index storing a bit array per distinct value, efficient for low-cardinality columns in read-heavy analytic workloads.Advanced
• BlockingA situation in which one session waits for a lock held by another session; it resolves when the holder finishes.Intermediate
• BookmarkA saved state of a Power BI report page (filters, slicers, visibility, sort) that users can return to, often used for navigation and storytelling.Intermediate
• BootstrappingEstimating the sampling distribution of a statistic by repeatedly resampling the observed data with replacement.Advanced
• Box PlotA chart showing a distribution's median, quartiles (the box), whiskers and outliers; also called a box-and-whisker plot.Foundational
• Boyce-Codd Normal Form (BCNF)A stricter version of 3NF in which every determinant (left side of a functional dependency) is a candidate key.Advanced
• Bridge TableA table that resolves a many-to-many relationship between a fact and a dimension, or handles multivalued dimensions.Advanced
• Broadcast JoinA join strategy that sends a copy of a small table to every executor so the large table is joined without being shuffled.Advanced
• Bronze LayerThe raw landing layer of a medallion architecture, holding source data as ingested, often append-only with load metadata.Intermediate
• BSONBinary JSON: MongoDB's binary-encoded document format, which adds types such as ObjectId, Date, Decimal128 and binary data.Intermediate
• Bullet ChartA compact bar chart, designed by Stephen Few, that shows a measure against a target and qualitative ranges.Advanced
• Bus MatrixA Kimball planning grid that lists business processes (rows) against conformed dimensions (columns) to design an integrated warehouse.Advanced
• Business GlossaryA governed list of business terms and their agreed definitions, owners and relationships, linked to the physical data assets that implement them.Intermediate
• Business Intelligence (BI)The technologies and practices for collecting, integrating, analyzing and presenting business data to support decision-making.Foundational
• Caching StrategyPatterns for keeping a cache consistent with a database, such as cache-aside (lazy loading), write-through and write-behind.Intermediate
• CALCULATE FunctionThe DAX function that evaluates an expression in a modified filter context, adding, replacing or removing filters.Advanced
• Calculated ColumnA DAX column computed row by row at data refresh and stored in the model, usable in slicers, filters and axes.Intermediate
• Calculated Field (Tableau)A new Tableau field created from a formula using functions, operators and other fields.Foundational
• Calculated TableA table created with a DAX expression evaluated at refresh, such as a date table from CALENDAR or CALENDARAUTO.Advanced
• Calculation GroupsA semantic model feature that applies reusable DAX logic (calculation items) to any measure, reducing measure proliferation.Advanced
• Candidate KeyAny minimal set of columns that could uniquely identify every row; one is chosen as the primary key.Intermediate
• CAP TheoremThe principle that a distributed data store can guarantee at most two of Consistency, Availability and Partition tolerance during a network partition.Intermediate
• Cardinality (Data Modeling)The number of instances of one entity that can relate to instances of another: one-to-one, one-to-many or many-to-many.Foundational
• Cartesian ProductThe set of all possible row pairings between two tables, produced by a cross join or a missing join condition.Intermediate
• Cascading Referential ActionForeign key options (CASCADE, SET NULL, SET DEFAULT, NO ACTION, RESTRICT) that define what happens to child rows when a parent row changes.Intermediate
• CASE ExpressionSQL's conditional expression, which returns a value based on the first WHEN condition that is true.Foundational
• CAST FunctionThe ANSI SQL function that explicitly converts a value to another data type: CAST(expression AS type).Foundational
• Catalyst OptimizerSpark SQL's extensible optimizer, which turns logical plans into optimized physical plans using rule-based and cost-based optimization.Advanced
• Categorical Color PaletteA set of distinct hues for unordered categories, without implying magnitude or order.Intermediate
• Categorical DataQualitative data that place observations into groups (nominal or ordinal) rather than measuring quantities.Foundational
• Central Limit Theorem (CLT)The theorem that the distribution of sample means approaches a normal distribution as sample size grows, regardless of the population's shape.Intermediate
• Change Data Capture (Data Engineering) (CDC)Identifying and capturing row-level inserts, updates and deletes in a source so only changes are propagated downstream.Intermediate
• Change Data Feed (CDF)A Delta Lake feature that records row-level inserts, updates and deletes between table versions so downstream jobs can process only changes.Advanced
• Chart SelectionMatching the chart to the task: bar to compare, line for trends, histogram or box plot for distributions, scatter for relationships.Foundational
• ChartjunkUnnecessary or distracting decoration in charts, such as 3-D effects, heavy patterns or clip art, that doesn't convey data.Foundational
• Chasm TrapAn error that occurs when two fact tables are joined through a shared dimension, multiplying rows and overstating measures from both.Advanced
• Check ConstraintA rule that limits the values a column can accept to those that satisfy a Boolean expression.Intermediate
• CheckpointingPersisting a streaming query's progress (offsets) and state to durable storage so it can recover after failure.Advanced
• Chi-Square Test (χ²)A test for categorical data: goodness of fit (observed vs expected frequencies) or independence (association between two categorical variables).Intermediate
• Choropleth MapA map that shades geographic regions by a data value.Intermediate
• Cloud ComposerGoogle Cloud's fully managed Apache Airflow service for orchestrating workflows across Google Cloud and external systems.Intermediate
• Cloud Services LayerThe Snowflake layer that coordinates authentication, infrastructure, metadata, query parsing and optimization, access control and the result cache.Intermediate
• Cluster SamplingDividing the population into clusters (such as schools or stores), randomly selecting whole clusters, and sampling everyone (or a sample) within them.Intermediate
• Clustered IndexAn index that determines the physical order in which table rows are stored, so the table itself becomes the index's leaf level.Intermediate
• Clustering DepthThe average number of overlapping micro-partitions for given column values; lower depth means better clustering.Advanced
• Clustering KeyOne or more columns or expressions designated to co-locate similar rows in the same micro-partitions of a large Snowflake table, improving pruning.Advanced
• COALESCE FunctionA function that returns the first non-NULL argument in its list.Foundational
• Coefficient of Variation (CV)The standard deviation divided by the mean, often given as a percentage, used to compare variability across datasets with different scales.Intermediate
• Cohort AnalysisGrouping users by a shared starting event or period, such as signup month, and tracking their behavior over time.Intermediate
• ColumnA named attribute of a table with a defined data type that every row stores a value (or NULL) for; also called a field.Foundational
• Column AliasA temporary name given to a column or expression in a query's result using AS.Foundational
• Column CardinalityThe number of distinct values in a column; high cardinality means many unique values.Intermediate
• Column-Level SecurityRestricting access to specific columns, for example through column GRANTs, masking policies or object-level security.Intermediate
• Columnar StorageStoring each column's values together on disk rather than storing whole rows, which speeds analytic scans and improves compression.Intermediate
• Columnstore IndexA SQL Server and Azure SQL index that stores data column by column in compressed segments for fast analytic scans.Advanced
• COMMIT StatementThe TCL command that makes all changes in the current transaction permanent and visible to other sessions.Foundational
• Common Table Expression (CTE)A named temporary result set defined with WITH that can be referenced in the statement that follows.Intermediate
• Composite IndexAn index built on two or more columns, ordered by the first column, then the second, and so on.Intermediate
• Composite KeyA key made of two or more columns that together uniquely identify a row.Intermediate
• Composite ModelA Power BI model that combines storage modes, such as Import and DirectQuery tables, or that chains to other published semantic models.Advanced
• Conceptual Data ModelA high-level model that shows the main business entities and their relationships, without attributes or technical detail.Foundational
• Conditional ProbabilityThe probability of an event given that another event has occurred: P(A|B) = P(A and B) / P(B).Intermediate
• Confidence Interval (CI)A range computed from sample data that, under repeated sampling, would contain the true population parameter a stated percentage of the time.Intermediate
• Conformed DimensionA dimension shared with consistent keys, attributes and meaning across multiple fact tables or data marts.Intermediate
• Confounding VariableA variable that influences both the supposed cause and the effect, creating a spurious association.Intermediate
• Connection PoolingReusing a pool of open database connections across requests instead of opening a new connection each time.Intermediate
• Consistency (ACID)The ACID property that a transaction takes the database from one valid state to another, respecting all constraints and rules.Foundational
• Consumer GroupA set of consumers that share the work of reading a topic, with each partition assigned to one consumer in the group.Advanced
• Context FilterA Tableau filter promoted to run before other filters, creating an independent subset that later filters, Top N and FIXED LODs work against.Advanced
• Context TransitionThe DAX behavior in which CALCULATE, or a measure reference, converts the current row context into an equivalent filter context.Advanced
• Continuous DataQuantitative data that can take any value within a range, such as height, time or temperature.Foundational
• Convenience SamplingA non-probability method that samples whoever is easiest to reach.Foundational
• COPY INTOThe command that bulk-loads staged files into a table (COPY INTO <table>) or unloads query results to a stage (COPY INTO <location>).Intermediate
• Correlated SubqueryA subquery that references columns from the outer query and is logically evaluated once per outer row.Intermediate
• Correlation CoefficientPearson's r: a value from -1 to +1 measuring the strength and direction of a linear relationship between two numeric variables.Intermediate
• Correlation vs CausationThe principle that a statistical association between two variables does not prove that one causes the other.Foundational
• COUNT FunctionAn aggregate that counts rows: COUNT(*) counts every row, COUNT(col) counts non-null values, COUNT(DISTINCT col) counts unique non-null values.Foundational
• Covering IndexAn index that contains every column a query needs, so the query can be answered from the index alone.Advanced
• CREATE TABLE AS SELECT (CTAS)A statement that creates a new table and fills it with the results of a query in one step.Intermediate
• CREATE TABLE StatementThe DDL statement that defines a new table with its columns, data types and constraints.Foundational
• CRISP-DMCross-Industry Standard Process for Data Mining: six iterative phases from business understanding through data prep, modeling, evaluation and deployment.Intermediate
• CROSS JOINA join with no condition that returns every combination of rows from both tables (the Cartesian product).Intermediate
• Cross-Filter DirectionThe direction in which a Power BI relationship propagates filters: single (one side to many side) or both (bidirectional).Advanced
• Crow's Foot NotationAn ERD notation that uses symbols at line ends to show cardinality: a three-pronged 'crow's foot' for many, a bar for one and a circle for zero.Intermediate
• CursorA database object that lets procedural code process a query result one row at a time.Advanced
• Cypher Query LanguageA declarative graph query language, created by Neo4j, that uses ASCII-art patterns such as (a)-[:REL]->(b) to match nodes and relationships.Advanced
• DAMA-DMBOKThe Data Management Body of Knowledge published by DAMA International, which defines data management knowledge areas with data governance at the center.Intermediate
• Dashboard (Data Visualization)A visual display of the most important information needed to achieve objectives, arranged on a single screen for at-a-glance monitoring.Foundational
• Dashboard ActionsInteractivity rules in Tableau dashboards: filter, highlight, URL, go to sheet, parameter and set actions triggered by hover, select or menu.Intermediate
• Data AccuracyThe data quality dimension measuring how well data values reflect the real-world entities or events they describe.Foundational
• Data Analysis Expressions (DAX)The formula language of Power BI, Analysis Services Tabular and Power Pivot, used for measures, calculated columns, calculated tables and security rules.Intermediate
• Data Analysis ProcessA structured analytics workflow; the Google Data Analytics certificate's six phases are Ask, Prepare, Process, Analyze, Share and Act.Foundational
• Data AnomaliesInsert, update and delete anomalies: integrity problems caused by redundant data in unnormalized tables.Intermediate
• Data ArchivingMoving data that is no longer actively used to lower-cost, long-term storage while keeping it retrievable for compliance or reference.Foundational
• Data BlendingA Tableau technique that combines data from separate data sources at the aggregate level of the view, linked on common dimensions.Intermediate
• Data CatalogAn inventory of an organization's data assets with metadata, descriptions, ownership, classifications, lineage and search for discovery.Intermediate
• Data Clean RoomA secure environment where multiple parties can run approved joint analyses on combined data without exposing raw records to each other.Advanced
• Data CleansingDetecting and correcting or removing inaccurate, incomplete, duplicate or improperly formatted data.Foundational
• Data CompletenessThe data quality dimension measuring whether all required data values and records are present.Foundational
• Data ConsistencyThe data quality dimension measuring whether the same data agrees across records, systems and time.Foundational
• Data ContractA formal agreement between data producers and consumers that specifies schema, semantics, quality expectations, SLAs and change management for a dataset.Advanced
• Data Control Language (DCL)The SQL commands that manage permissions: GRANT, REVOKE and, in SQL Server, DENY.Foundational
• Data Definition Language (DDL)The SQL commands that define and change database structure: CREATE, ALTER, DROP, TRUNCATE and RENAME.Foundational
• Data DemocratizationMaking data accessible to non-technical users across an organization, with appropriate governance.Foundational
• Data DictionaryA repository of metadata describing each table, column, data type, constraint and meaning in a database.Foundational
• Data FabricAn architecture that uses metadata, automation and integration services to provide unified, governed access to data across distributed sources.Advanced
• Data FederationRunning a single query across multiple independent databases and returning combined results.Intermediate
• Data FreshnessHow recently data was updated relative to expectations, usually monitored as the time since the last successful load.Intermediate
• Data GovernanceThe framework of policies, roles, standards, processes and controls that ensures data is managed as an asset: secure, high quality, compliant and usable.Foundational
• Data IngestionThe process of importing data from sources into a storage or processing platform, in batches or as a stream.Foundational
• Data LakeA central repository that stores large volumes of raw data in any format (structured, semi-structured or unstructured) cheaply, usually in object storage.Foundational
• Data LakehouseAn architecture that adds warehouse features such as ACID transactions, schema enforcement and fast SQL to low-cost data lake storage using open table formats.Intermediate
• Data Lifecycle Management (DLM)Managing data from creation and storage through use, sharing, archiving and secure deletion according to policy.Intermediate
• Data LiteracyThe ability to read, work with, analyze and communicate with data.Foundational
• Data Manipulation Language (SQL) (DML)The SQL commands that add, change or remove rows: INSERT, UPDATE, DELETE and MERGE (and, in some classifications, SELECT).Foundational
• Data MartA subset of a data warehouse focused on one business area or department, such as sales or finance.Foundational
• Data MeshA decentralized sociotechnical approach in which domain teams own and serve their data as products on a self-service platform, with federated governance.Advanced
• Data ObservabilityContinuous monitoring of data health across pipelines (freshness, volume, schema, distribution and lineage) to detect and resolve issues quickly.Intermediate
• Data OrchestrationCoordinating the scheduling, dependencies, retries and monitoring of data pipeline tasks.Intermediate
• Data ParsingBreaking a string or semi-structured value into components, such as splitting a full address into street, city and postal code.Foundational
• Data PipelineAn automated series of steps that moves data from sources through transformations to destinations.Foundational
• Data ProductA curated, discoverable, trustworthy dataset or service owned by a domain team and published for others to consume.Intermediate
• Data ProfilingExamining data to summarize its structure, content, completeness, distributions, patterns and anomalies before using it.Foundational
• Data ProvenanceThe documented origin and history of data, including where it came from, who created or changed it, and how.Intermediate
• Data Quality (DQ)The degree to which data is fit for its intended use, judged on dimensions such as accuracy, completeness, consistency, timeliness, validity and uniqueness.Foundational
• Data Quality DimensionsMeasurable aspects of data quality: accuracy, completeness, consistency, timeliness, validity and uniqueness.Foundational
• Data Query Language (DQL)The SQL sublanguage for retrieving data, consisting essentially of the SELECT statement.Foundational
• Data SiloData isolated within one department or system and not accessible or integrated with the rest of the organization.Foundational
• Data SkewAn uneven distribution of data across partitions, so a few tasks process far more data and slow the whole job.Advanced
• Data SkippingUsing per-file min/max statistics to skip files that cannot contain rows matching a query filter.Advanced
• Data StandardizationConverting data into a consistent format and set of codes, such as ISO dates, country codes, units and naming conventions.Foundational
• Data StorytellingCommunicating insights by combining data, visuals and narrative tailored to an audience to drive understanding and action.Foundational
• Data SwampA data lake that has become unusable because of missing metadata, governance and quality controls.Foundational
• Data TimelinessThe data quality dimension measuring whether data is available and current enough for its intended use.Foundational
• Data TransformationConverting data from one structure, format or value set to another, by filtering, joining, aggregating, pivoting, deriving or recoding.Foundational
• Data UniquenessThe data quality dimension measuring whether each real-world entity is recorded only once.Foundational
• Data ValidityThe data quality dimension measuring whether values conform to defined formats, types, ranges and business rules.Foundational
• Data VaultA modeling method for agile, auditable warehouses that separates business keys (hubs), relationships (links) and descriptive history (satellites).Advanced
• Data Vault HubA Data Vault table that stores the unique list of business keys for a core business concept, with a hash key, load date and record source.Advanced
• Data Vault LinkA Data Vault table that records relationships or transactions between two or more hubs.Advanced
• Data Vault SatelliteA Data Vault table that stores descriptive attributes and their full change history for a hub or link.Advanced
• Data VirtualizationQuerying data in place across multiple sources through a unified layer, without physically copying it.Intermediate
• Data VisualizationRepresenting data graphically so that patterns, trends, comparisons and outliers can be understood quickly.Foundational
• Data Warehouse (DW)A central repository of integrated, cleaned, historical data from multiple sources, structured for analytics and reporting.Foundational
• Data WranglingThe overall process of discovering, structuring, cleaning, enriching and validating raw data into an analysis-ready form; also called data munging.Foundational
• Data-Ink RatioEdward Tufte's principle that the share of a graphic's ink devoted to data should be maximized and non-data ink minimized.Intermediate
• Database AuditingTracking and recording database events such as logins, queries, permission changes and data modifications for security and compliance.Intermediate
• Database IndexA data structure that speeds up row lookups on one or more columns at the cost of extra storage and slower writes.Foundational
• Database NormalizationThe process of organizing tables to reduce redundancy and prevent update anomalies by applying normal forms.Foundational
• Database SchemaThe structure of a database (its tables, columns, types, keys and relationships), or a named namespace that groups database objects.Foundational
• Database StatisticsMetadata about the distribution of values in columns and indexes, used by the optimizer to estimate row counts.Advanced
• Database TableThe core relational storage object: a named set of rows sharing the same columns; formally called a relation.Foundational
• Database TransactionA logical unit of work of one or more operations that must succeed or fail as a whole.Foundational
• Databricks Asset Bundles (DABs)A Databricks infrastructure-as-code format that defines jobs, pipelines and other resources in YAML for versioned CI/CD deployment across environments.Advanced
• Databricks SQL WarehouseDatabricks compute optimized for SQL analytics and BI, available as serverless, pro or classic, with Photon and intelligent workload management.Intermediate
• Dataflow Gen2Fabric's low-code data preparation item that uses Power Query Online to ingest and transform data and write it to lakehouses, warehouses and more.Intermediate
• Dataplex Universal CatalogGoogle Cloud's intelligent data governance service for discovering, cataloging, profiling, checking quality and managing lineage across data.Advanced
• DataprocGoogle Cloud's managed Spark and Hadoop service, with fast cluster creation, autoscaling and a serverless Spark option.Intermediate
• Date DimensionA dimension with one row per calendar date and attributes such as year, quarter, month, weekday, fiscal period and holiday flag.Foundational
• DAX MeasureA DAX calculation evaluated at query time in the filter context of each visual cell; it is not stored in the model.Intermediate
• dbtA transformation framework (data build tool) where analysts write SQL SELECT models that run in the warehouse, with tests, docs and lineage.Intermediate
• DeadlockA cycle in which two or more transactions each hold a lock the other needs, so none can proceed.Intermediate
• Decomposition TreeA Power BI AI visual that lets users break a measure down across dimensions in any order, with AI splits suggesting the highest or lowest values.Advanced
• Default ConstraintA constraint that supplies a value for a column when an INSERT does not specify one.Foundational
• Degenerate DimensionA dimension key, such as an order or invoice number, stored in the fact table with no separate dimension table.Advanced
• DELETE StatementThe DML statement that removes rows that match a condition from a table, logging each row.Foundational
• Delimited Text FileA plain-text file, such as CSV or TSV, in which fields are separated by a delimiter and records by line breaks.Foundational
• Delta LakeAn open-source table format that adds ACID transactions, schema enforcement and evolution, time travel and MERGE to Parquet files.Intermediate
• Delta Lake Time TravelQuerying or restoring earlier versions of a Delta table by version number or timestamp.Intermediate
• Delta SharingAn open protocol for securely sharing live Delta Lake and other data with any platform, without copying it.Advanced
• Delta Transaction LogThe _delta_log folder of ordered JSON commit files and Parquet checkpoints that records every change to a Delta table and provides ACID guarantees.Advanced
• DenormalizationIntentionally adding redundancy, for example by merging tables or duplicating columns, to speed reads and simplify queries.Intermediate
• Deployment PipelinesA Power BI and Fabric feature for promoting content through development, test and production workspaces, with deployment rules for data sources and parameters.Advanced
• Derived TableA subquery in the FROM clause that acts as a temporary inline table, which must have an alias.Intermediate
• Descriptive AnalyticsAnalytics that answers 'what happened?' by summarizing historical data through reports, dashboards and KPIs.Foundational
• Descriptive StatisticsStatistics that summarize and describe the features of a dataset, such as its center, spread and shape, without generalizing beyond it.Foundational
• Diagnostic AnalyticsAnalytics that answers 'why did it happen?' through drill-down, correlation, segmentation and root-cause analysis.Foundational
• Dimension TableA table of descriptive attributes (who, what, where, when) used to filter, group and label facts.Foundational
• Dimensional ModelingA data modeling technique that organizes analytic data into facts (measurable events) and dimensions (descriptive context).Intermediate
• Dimensions and Measures (Tableau)Tableau's field roles: dimensions are qualitative values that slice the view; measures are quantitative values that are aggregated.Foundational
• Direct LakeA Fabric storage mode in which semantic models load Delta Parquet column data directly from OneLake into memory on demand, without import refresh.Advanced
• Directed Acyclic Graph (DAG)A graph of tasks with directed dependencies and no cycles, used to define pipeline workflows and execution plans.Intermediate
• DirectQueryA Power BI storage mode that sends queries to the source at report time instead of importing data, keeping results current.Intermediate
• Dirty ReadReading data written by another transaction that has not yet committed and may be rolled back.Intermediate
• Discrete and Continuous FieldsTableau field types: discrete (blue pills) create headers and distinct values; continuous (green pills) create axes.Foundational
• Discrete DataQuantitative data that take countable values, usually integers, such as number of orders or defects.Foundational
• DISTINCT KeywordA SELECT modifier that removes duplicate rows from the result.Foundational
• Distributed TransactionA transaction that spans multiple databases or nodes and must still be atomic across all of them.Advanced
• Diverging Color PaletteA two-hue color scale with a neutral midpoint, used for data that deviates above and below a meaningful center such as zero or a target.Intermediate
• Document DatabaseA NoSQL database that stores self-describing documents (JSON or BSON) whose structure can vary from document to document.Foundational
• Document EmbeddingStoring related data inside a parent document (embedding) rather than in a separate collection with references.Intermediate
• Domain IntegrityThe rule that every column value comes from the column's valid set of values, enforced by data types, CHECK, NOT NULL and DEFAULT.Intermediate
• Drill-DownNavigating from summarized data to a more detailed level along a hierarchy, such as Year to Quarter to Month.Foundational
• Drill-ThroughNavigating from a summary value to a separate detail page or report, filtered to the selected context.Intermediate
• DROP StatementThe DDL command that permanently removes a database object, such as a table, view, index or schema, together with its data.Foundational
• DTU Purchasing ModelAn Azure SQL Database pricing model that bundles CPU, memory and I/O into Database Transaction Units across Basic, Standard and Premium tiers.Intermediate
• Dual Axis ChartA chart that overlays two measures with independent axes on the same pane, often with different mark types.Intermediate
• Dual Storage ModeA Power BI table storage mode that can act as Import or DirectQuery depending on the query, which avoids weak relationships in composite models.Advanced
• Duplicate Record DetectionIdentifying records that represent the same entity, through exact key matches or fuzzy matching of attributes.Intermediate
• DurabilityThe ACID property that committed changes persist even after a crash or power loss.Foundational
• Dynamic Data Masking (DDM)Masking sensitive column values in query results for unauthorized users at run time without changing the stored data.Intermediate
• Dynamic Row-Level SecurityRLS that filters data using the signed-in user's identity, typically through USERPRINCIPALNAME() and a user-to-entitlement mapping table.Advanced
• Dynamic SQLSQL statements built as strings at run time and then executed, for example with EXEC, sp_executesql or EXECUTE IMMEDIATE.Advanced
• Dynamic TableA Snowflake table defined by a query that Snowflake keeps refreshed automatically to meet a declared target lag.Advanced
• Effect SizeA measure of the magnitude of a difference or relationship, independent of sample size, such as Cohen's d or a correlation coefficient.Advanced
• Embedded AnalyticsIntegrating dashboards and reports directly into other applications or portals.Intermediate
• Empirical RuleThe 68-95-99.7 rule: in a normal distribution about 68%, 95% and 99.7% of values lie within 1, 2 and 3 standard deviations of the mean.Foundational
• EndorsementPower BI and Fabric badges (Promoted, Certified and Master data) that signal trustworthy content to users.Intermediate
• Enterprise Data Warehouse (EDW)An organization-wide data warehouse that integrates data across all business areas to serve as a single source for analytics.Intermediate
• EntityA person, place, thing, event or concept about which data is stored; it usually becomes a table.Foundational
• Entity IntegrityThe relational rule that every table has a primary key and that no primary key value is NULL or duplicated.Intermediate
• Entity ResolutionDetermining when records from one or many sources refer to the same real-world entity and linking or merging them.Advanced
• Entity-Relationship Diagram (ERD)A diagram that shows entities, their attributes and the relationships between them, used to design databases.Foundational
• Event TimeThe time an event actually occurred at its source, as opposed to processing time, when the system handles it.Advanced
• EventhouseA Fabric item hosting one or more KQL databases optimized for high-volume, time-based event and log analytics.Advanced
• EventstreamA Fabric item that captures, transforms and routes real-time event data from sources such as Event Hubs, IoT Hub, Kafka and CDC to destinations without code.Advanced
• Eventual ConsistencyA model in which replicas converge to the same value if no new updates occur, but reads may temporarily return stale data.Intermediate
• Exactly-Once Semantics (EOS)A processing guarantee that each record affects the output exactly one time despite failures and retries.Advanced
• EXCEPT OperatorA set operator that returns distinct rows from the first query that are not in the second; Oracle calls it MINUS.Intermediate
• EXISTS OperatorA predicate that returns true if a subquery returns at least one row.Intermediate
• Expected Value (EV)The probability-weighted average of all possible outcomes of a random variable: E[X] = Σ x × P(x).Intermediate
• Exploratory Data Analysis (EDA)An open-ended investigation of a dataset with summary statistics and visualizations to understand structure, spot anomalies and form hypotheses.Foundational
• Exponential SmoothingA forecasting method that weights observations with exponentially decreasing weights, with variants for trend (Holt) and seasonality (Holt-Winters).Advanced
• External TableA table whose data files reside in external storage and are queried in place, with only metadata kept in the database.Intermediate
• Extract, Load, Transform (ELT)A pattern that loads raw data into the target platform first and transforms it there using the platform's own compute.Foundational
• Extract, Transform, Load (ETL)A data integration process that extracts data from sources, transforms it in a separate engine, then loads it into a target such as a warehouse.Foundational
• Fabric CapacityThe pool of compute (F SKUs measured in Capacity Units) that powers all Fabric workloads in assigned workspaces.Advanced
• Fabric LakehouseA Fabric item that stores files and Delta tables in OneLake, processed with Spark, and automatically exposes a read-only SQL analytics endpoint.Intermediate
• Fabric WarehouseA Fabric item that provides a fully transactional T-SQL data warehouse that stores data as Delta tables in OneLake.Intermediate
• Fact TableThe central table in a star schema that stores numeric measurements of business events plus foreign keys to dimensions.Foundational
• Factless Fact TableA fact table with dimension keys but no numeric measures, recording that an event or coverage relationship occurred.Advanced
• Failover Cluster Instance (FCI)A SQL Server instance installed across clustered nodes with shared storage, so the entire instance fails over to another node.Advanced
• Fan TrapA modeling or join error in which joining tables at different grains duplicates rows and inflates aggregated totals.Advanced
• Field ParametersA Power BI feature that lets report users switch which measures or dimensions a visual displays through a slicer.Advanced
• File Format ObjectA named Snowflake object that stores parsing options (type, delimiter, compression, header skipping, NULL handling) for loading and unloading files.Intermediate
• Fill FactorThe percentage of each index leaf page that SQL Server fills when building or rebuilding an index, leaving the rest free for growth.Advanced
• Filter ContextThe set of filters applied to the model when a DAX measure is evaluated, coming from visuals, slicers, filters, RLS and CALCULATE.Advanced
• First Normal Form (1NF)A table is in 1NF when every column holds atomic (single) values, there are no repeating groups, and each row is unique.Foundational
• Five Vs of Big DataThe characteristics of big data: Volume, Velocity, Variety, Veracity and Value.Foundational
• Five-Number SummaryA distribution summary consisting of the minimum, Q1, median, Q3 and maximum.Foundational
• FIXED LODA Tableau LOD expression that aggregates at exactly the listed dimensions, ignoring the view's dimensions.Advanced
• FLATTEN FunctionA Snowflake table function that explodes arrays or objects in VARIANT columns into one row per element.Intermediate
• Foreign Key (FK)A column in one table that references the primary or unique key of another table, enforcing a relationship between them.Foundational
• Fourth Normal Form (4NF)A table is in 4NF when it is in BCNF and has no non-trivial multivalued dependencies.Advanced
• Full LoadReloading an entire dataset each run, typically by truncating and repopulating the target.Foundational
• FULL OUTER JOINA join that returns all rows from both tables, matching where possible and filling NULLs on whichever side has no match.Intermediate
• Full Table ScanReading every row of a table to answer a query, typically because no usable index exists or most rows are needed.Intermediate
• Full-Text IndexAn index that supports fast word- and phrase-based searches inside large text columns.Intermediate
• Functional DependencyA relationship where the value of one attribute (or set) uniquely determines the value of another: X -> Y.Intermediate
• Funnel AnalysisMeasuring how users progress through sequential steps toward a goal and where they drop off.Intermediate
• Funnel ChartA chart of stages in a sequential process showing decreasing values, used for conversion pipelines.Foundational
• Galaxy SchemaA model with multiple fact tables that share conformed dimension tables; also called a fact constellation.Intermediate
• Gold LayerThe curated medallion layer that holds business-level aggregates and dimensional models ready for BI and reporting.Intermediate
• Google Cloud DataflowGoogle Cloud's serverless, autoscaling service for running Apache Beam pipelines for unified batch and stream processing.Intermediate
• GrainThe level of detail one row of a fact table represents, such as one line item per order or one balance per account per day.Intermediate
• GRANT StatementThe DCL statement that gives privileges on database objects to users or roles.Foundational
• Graph DatabaseA database that stores data as nodes and edges with properties, optimized for traversing relationships.Intermediate
• GROUP BY ClauseThe clause that groups rows sharing the same values so that aggregate functions return one row per group.Foundational
• GROUPING SETSA GROUP BY extension that lists exactly which groupings to compute in a single query.Advanced
• Hadoop Distributed File System (HDFS)Hadoop's distributed file system, which splits files into large blocks replicated across DataNodes, with a NameNode tracking metadata.Intermediate
• Half-Open Date RangeA date filter written as >= start AND < end, which includes the start and excludes the end so datetime values are captured correctly.Intermediate
• Hash IndexAn index that maps keys through a hash function to buckets, giving very fast equality lookups but no range support.Advanced
• HAVING ClauseThe clause that filters groups after GROUP BY, typically using aggregate conditions.Foundational
• Heat MapA matrix visualization in which cell color intensity encodes values, revealing patterns across two dimensions.Foundational
• HeteroscedasticityNon-constant variance of regression residuals across the range of predicted values.Advanced
• High-Water Mark (Incremental Load)The last processed value of a monotonically increasing column, such as a modified timestamp or ID, stored to drive the next incremental extract.Intermediate
• Hive Metastore (HMS)A central repository of table definitions, schemas, partitions and file locations used by Hive, Spark and other engines.Advanced
• Horizontal PartitioningSplitting a table by rows into several partitions or tables with the same columns.Intermediate
• Hot PartitionA partition or shard that receives a disproportionate share of traffic, creating a bottleneck while others sit idle.Advanced
• Hypothesis TestingA statistical procedure for deciding whether sample evidence is strong enough to reject a null hypothesis about a population.Intermediate
• Idempotent PipelineA pipeline that produces the same result no matter how many times it runs on the same input.Advanced
• Identity ColumnA column whose values the database generates automatically, typically incrementing integers, often used as a surrogate key.Intermediate
• Implicit ConversionAutomatic conversion of one data type to another by the database engine when an expression mixes types.Intermediate
• Import ModeA Power BI storage mode that loads compressed data into the in-memory VertiPaq engine for the fastest query performance.Foundational
• IN OperatorA predicate that tests whether a value matches any value in a list or subquery.Foundational
• In-Memory DatabaseA database that keeps its primary data in RAM for microsecond to millisecond access, often with optional persistence.Intermediate
• Incremental LoadLoading only data that is new or changed since the last run, instead of reloading everything.Intermediate
• Incremental RefreshA Power BI policy that refreshes only recent partitions of large Import tables while keeping historical partitions, using RangeStart and RangeEnd parameters.Advanced
• Index FragmentationDisorder in index pages, either logical (pages out of order) or low page density, which reduces scan efficiency.Advanced
• Index SeekAn access method that navigates an index tree directly to the matching keys instead of reading the whole index or table.Advanced
• Inferential StatisticsUsing sample data to draw conclusions or make predictions about a larger population, with quantified uncertainty.Foundational
• Inmon MethodologyBill Inmon's top-down approach that builds a normalized (3NF) enterprise data warehouse first, then derives dimensional data marts.Intermediate
• INNER JOINA join that returns only rows with matching values in both tables.Foundational
• INSERT StatementThe DML statement that adds new rows to a table, from literal values or from a SELECT.Foundational
• Integration Runtime (IR)The compute infrastructure Azure Data Factory and Synapse use for data movement and activity dispatch: Azure, self-hosted or Azure-SSIS.Advanced
• Interquartile Range (IQR)The spread of the middle 50% of data: the third quartile minus the first quartile (Q3 - Q1).Foundational
• INTERSECT OperatorA set operator that returns only the distinct rows present in both query results.Intermediate
• Inverted IndexA mapping from each term to the list of documents or rows that contain it, used by search engines and full-text indexes.Intermediate
• Isolation (ACID)The ACID property that concurrent transactions do not see each other's intermediate, uncommitted changes.Foundational
• Iterator FunctionsDAX functions ending in X (SUMX, AVERAGEX, COUNTX, MAXX, RANKX) that evaluate an expression row by row over a table and then aggregate.Advanced
• JSON DocumentA self-describing record in JavaScript Object Notation made of key-value pairs, arrays and nested objects.Foundational
• Junction TableAn associative table that resolves a many-to-many relationship by holding foreign keys to both related tables.Intermediate
• Junk DimensionA dimension that combines miscellaneous low-cardinality flags and indicators into one table to avoid cluttering the fact table.Advanced
• Kafka TopicA named, partitioned, append-only log in Kafka to which producers write and from which consumers read.Intermediate
• Kappa ArchitectureA simplification of Lambda architecture that treats all data as a stream and reprocesses history by replaying the log.Advanced
• Key Influencers VisualA Power BI AI visual that identifies and ranks the factors that most influence a target metric or outcome.Advanced
• Key LookupAn execution-plan operation in which the engine uses a nonclustered index and then fetches the remaining columns from the clustered index for each row.Advanced
• Key-Value StoreA NoSQL database that stores data as unique keys mapped to opaque values, optimized for fast lookups by key.Foundational
• Kimball MethodologyRalph Kimball's bottom-up approach that builds a data warehouse from dimensional star schemas linked by conformed dimensions.Intermediate
• KPI CardA visual that displays a key metric's current value, often against a target and with trend or status indicators.Foundational
• KurtosisA measure of the tailedness of a distribution relative to a normal distribution.Advanced
• LAG and LEAD FunctionsWindow functions that return a value from a previous row (LAG) or a following row (LEAD) within a partition.Intermediate
• Lakeflow Declarative PipelinesDatabricks' declarative ETL framework (formerly Delta Live Tables) where you define tables and the platform manages orchestration and data quality.Intermediate
• Lakeflow JobsDatabricks' orchestration service, formerly Workflows/Jobs, for scheduling multi-task DAGs of notebooks, SQL, pipelines, dbt and Python tasks.Intermediate
• Lakehouse FederationA Databricks feature that queries external databases (PostgreSQL, Snowflake, SQL Server) through Unity Catalog foreign catalogs without ingesting data.Advanced
• Lambda ArchitectureA big data architecture with a batch layer for accurate historical views and a speed layer for real-time views, merged in a serving layer.Advanced
• Late-Arriving DataRecords that arrive after the window or batch for their event time has already been processed.Advanced
• LATERAL JoinA join in which the right-hand table expression can reference columns from preceding tables in the FROM clause.Advanced
• Lazy EvaluationDeferring execution of transformations until an action requires a result, which lets the engine optimize the whole plan.Intermediate
• LEFT OUTER JOINA join that returns every row from the left table plus matching rows from the right, with NULLs where no match exists.Foundational
• Leftmost Prefix RuleThe principle that a composite index can be used for seeks only when queries filter on its leading column(s).Advanced
• Level of Detail Expression (LOD)A Tableau calculation that computes aggregates at a specified level of detail independent of the view: FIXED, INCLUDE or EXCLUDE.Advanced
• Levels of MeasurementThe four scales of data: nominal (labels), ordinal (ordered categories), interval (equal spacing, no true zero) and ratio (equal spacing with a true zero).Foundational
• LIKE OperatorA predicate that matches strings against a pattern using wildcards: % for any sequence and _ for a single character.Foundational
• LIMIT ClauseA clause that restricts how many rows a query returns; the syntax varies (LIMIT, TOP, FETCH FIRST n ROWS ONLY).Foundational
• Line ChartA chart that connects data points with lines to show trends over a continuous dimension, usually time.Foundational
• Liquid ClusteringA Delta Lake data layout feature that incrementally clusters data by chosen keys, which can be changed without rewriting the table.Advanced
• Live ConnectionQuerying the data source directly each time a view is rendered, so results reflect current data.Foundational
• LockingThe mechanism that controls concurrent access by placing shared (read) or exclusive (write) locks on resources.Intermediate
• Log ShippingA disaster-recovery method that automatically backs up transaction logs on a primary and restores them on secondary servers.Advanced
• Logical Data ModelA detailed, technology-independent model that defines entities, attributes, keys, relationships and normalization.Intermediate
• LookerGoogle Cloud's enterprise BI platform built on LookML, a semantic modeling layer that defines governed metrics over SQL databases.Intermediate
• Looker StudioGoogle's free, self-service dashboard and reporting tool (formerly Data Studio) that connects to Google Sheets, BigQuery and many other sources.Foundational
• LookMLLooker's modeling language for defining dimensions, measures, joins (explores) and views over SQL tables.Advanced
• Lost UpdateAn anomaly in which two transactions read the same value and both write back, so one overwrites the other's change.Advanced
• M LanguagePower Query Formula Language: the functional, case-sensitive language behind every Power Query transformation.Intermediate
• Managed TableA table whose data files and metadata are both managed by the platform; dropping it deletes the data.Intermediate
• Many-to-Many Relationship (Database) (M:N)A relationship where many rows in one table relate to many rows in another; it is resolved with a junction table.Intermediate
• MapReduceA programming model that processes large datasets in parallel with a map phase producing key-value pairs and a reduce phase aggregating them.Intermediate
• Margin of Error (MOE)Half the width of a confidence interval: the critical value multiplied by the standard error.Foundational
• Mark as Date TableA Power BI setting that designates a table as the model's date table, validating a unique, contiguous date column for time intelligence.Intermediate
• Masking PolicyA Snowflake Enterprise schema-level object that dynamically masks column values at query time based on conditions such as the current role.Intermediate
• Massively Parallel Processing (MPP)An architecture that splits data and query work across many nodes that process their portions in parallel.Intermediate
• Master DataCore, relatively stable business entities shared across processes, such as customers, products, employees and locations.Foundational
• Materialized ViewA database object that stores the precomputed result of a query and refreshes it as base data changes.Intermediate
• MeanThe arithmetic average: the sum of values divided by the number of values.Foundational
• Measures of Central TendencySingle values that describe the center of a distribution: mean, median and mode.Foundational
• Medallion ArchitectureA lakehouse design pattern that refines data progressively through Bronze (raw), Silver (cleansed) and Gold (business-ready) layers.Intermediate
• MedianThe middle value of ordered data, or the average of the two middle values when the count is even.Foundational
• Merge QueriesA Power Query operation that joins two queries horizontally on matching columns, like a SQL join.Foundational
• MERGE StatementA single DML statement that inserts, updates or deletes target rows based on whether they match rows in a source.Intermediate
• MetadataData about data: technical (schemas, types), business (definitions, owners) and operational (load times, lineage, usage) information.Foundational
• Micro-Batch ProcessingA streaming approach that processes incoming data in very small, frequent batches.Intermediate
• Micro-PartitionSnowflake's immutable, automatically created columnar storage units, each holding 50-500 MB of uncompressed data with min/max metadata per column.Intermediate
• Microsoft FabricMicrosoft's unified SaaS analytics platform combining data engineering, integration, warehousing, real-time analytics, data science and Power BI on OneLake.Foundational
• Microsoft PurviewMicrosoft's unified data governance, security and compliance platform, including the Unified Catalog, Data Map, data lineage, sensitivity labels and DLP.Intermediate
• Mirroring in FabricA Fabric feature that continuously replicates operational databases (Azure SQL, Cosmos DB, Snowflake and others) into OneLake as Delta tables in near real time.Advanced
• Misleading VisualizationA chart that distorts the data's message through truncated or inconsistent axes, inappropriate scales, cherry-picked ranges or area distortion.Foundational
• ModeThe most frequently occurring value in a dataset; there may be none, one (unimodal) or several (multimodal).Foundational
• MongoDBA popular document database that stores BSON documents in collections and supports rich queries, indexes, aggregation and horizontal sharding.Foundational
• MongoDB Aggregation PipelineA MongoDB framework that processes documents through ordered stages such as $match, $group, $project, $sort, $lookup and $unwind.Intermediate
• Moving AverageThe average of the most recent n periods, recalculated each period to smooth short-term fluctuations and reveal trends.Foundational
• Multi-Cluster WarehouseA Snowflake Enterprise Edition warehouse that automatically adds or removes clusters, between a minimum and maximum, to handle concurrent users.Intermediate
• Multi-Model DatabaseA database that supports several data models, such as document, key-value, graph and column, behind one service.Intermediate
• MulticollinearityHigh correlation among predictor variables in a regression, which makes coefficient estimates unstable and hard to interpret.Advanced
• Multiple Linear RegressionA regression model that predicts a numeric outcome from two or more predictors: y = β0 + β1x1 + ... + βkxk + ε.Intermediate
• Multivalued Dependency (MVD)A constraint where one attribute determines a set of values for another attribute, independent of the other attributes.Advanced
• Multiversion Concurrency Control (MVCC)A concurrency method that keeps multiple versions of rows so readers see a consistent snapshot without blocking writers.Advanced
• N+1 Query ProblemA performance anti-pattern that runs one query to fetch N parent rows and then N more queries to fetch each one's children.Advanced
• Natural KeyA key made from real-world business data that is already unique, such as an ISBN, VIN or email address; also called a business key.Intermediate
• Non-Additive MeasureA fact that cannot be summed across any dimension, such as percentages, ratios or unit prices.Intermediate
• Non-Repeatable ReadAn anomaly in which reading the same row twice in one transaction returns different values because another transaction committed a change in between.Intermediate
• Nonclustered IndexA separate index structure containing key values and pointers to the data rows; a table can have many.Intermediate
• Normal DistributionA symmetric, bell-shaped continuous probability distribution fully described by its mean and standard deviation.Foundational
• NoSQL DatabaseA non-relational database that stores data as key-value pairs, documents, wide columns or graphs, usually with a flexible schema.Foundational
• NOT EXISTSA predicate that is true when a correlated subquery returns no rows; the NULL-safe way to write an anti join.Intermediate
• NOT NULL ConstraintA constraint requiring that a column always contains a value.Foundational
• NTILE FunctionA window function that divides ordered rows into a specified number of roughly equal buckets and returns each row's bucket number.Advanced
• NULLA marker meaning a value is missing or unknown; it is not zero, an empty string or false.Foundational
• Null Hypothesis (H0)The default assumption of no effect, no difference or no relationship, which a test tries to find evidence against.Foundational
• NULLIF FunctionA function that returns NULL if its two arguments are equal, otherwise the first argument.Intermediate
• Object TaggingAttaching key-value tags to Snowflake objects (accounts, warehouses, tables, columns) to track sensitive data, cost centers and ownership.Advanced
• Object-Level Security (OLS)Power BI semantic model security that hides entire tables or columns from specified roles.Advanced
• Object-Relational Mapping (ORM)A technique and set of libraries (Hibernate, Entity Framework, SQLAlchemy) that map programming objects to relational tables.Intermediate
• OLAP CubeA multidimensional data structure that precomputes measures across dimensions for fast slicing and aggregation.Intermediate
• On-Premises Data GatewaySoftware installed on a local machine that securely connects Power BI, Fabric, Power Apps and Logic Apps to on-premises data sources.Intermediate
• One-Tailed TestA hypothesis test in which the alternative specifies a direction (greater than or less than), so the rejection region lies in one tail.Intermediate
• One-to-Many Relationship (1:N)A relationship where one row in a parent table can relate to many rows in a child table, but each child relates to one parent.Foundational
• One-to-One Relationship (1:1)A relationship where each row in one table matches at most one row in another.Intermediate
• OneLakeFabric's single, tenant-wide logical data lake, built on ADLS Gen2, where all Fabric items store data in open Delta Parquet format.Intermediate
• OneLake ShortcutA Fabric pointer that makes data elsewhere (OneLake, ADLS Gen2, Amazon S3, Google Cloud Storage, Dataverse) appear in a lakehouse without copying it.Intermediate
• Online Analytical Processing (OLAP)Systems optimized for complex, read-heavy queries that aggregate large volumes of historical data for analysis.Foundational
• Online Transaction Processing (OLTP)Systems that handle many short, concurrent read and write transactions, such as orders, payments and bookings.Foundational
• Open Table FormatA metadata layer over data files (usually Parquet) that adds ACID transactions, schema evolution, time travel and efficient pruning to data lakes.Advanced
• Operational Data Store (ODS)An integrated, near-real-time store of current operational data from several systems, used for operational reporting.Intermediate
• Optimistic Concurrency ControlA strategy that lets transactions proceed without locks and checks for conflicts at write time using version numbers or timestamps.Advanced
• OPTIMIZE CommandA Delta Lake command that compacts small files into larger ones and optionally applies Z-ordering or liquid clustering.Advanced
• OptionalityWhether participation in a relationship is mandatory (minimum one) or optional (minimum zero).Intermediate
• ORDER BY ClauseThe clause that sorts the final result set by one or more expressions, ascending (default) or descending.Foundational
• Ordinal DataCategorical data with a meaningful order but unequal or unknown spacing between categories.Foundational
• Orphan RecordA child row whose foreign key points to a parent row that does not exist.Foundational
• OutlierAn observation that lies unusually far from the other values in a dataset.Foundational
• P-ValueThe probability, assuming the null hypothesis is true, of observing results at least as extreme as those in the sample.Intermediate
• PACELC TheoremAn extension of CAP: if there is a Partition, choose Availability or Consistency; Else, choose Latency or Consistency.Advanced
• Page SplitAn operation in which a full index page is divided in two to make room for a new row, causing fragmentation and extra logging.Advanced
• Paginated ReportA pixel-perfect, printable report format (RDL) built in Power BI Report Builder, designed for multi-page tables such as invoices or statements.Intermediate
• Paired t-TestA t-test on the differences between paired measurements of the same subjects, such as before and after a treatment.Advanced
• Parameterized QueryA query that uses placeholders for input values that are bound separately, so the input is never treated as SQL code.Intermediate
• Partial DependencyA dependency in which a non-key attribute depends on only part of a composite primary key.Intermediate
• Partition PruningSkipping partitions whose data cannot satisfy a query's filter, which reduces the data scanned.Intermediate
• PercentileThe value below which a given percentage of observations fall; the 90th percentile exceeds 90% of the values.Foundational
• Performance AnalyzerA Power BI Desktop pane that records how long each visual takes, broken into DAX query, visual display and other time.Intermediate
• Periodic Snapshot Fact TableA fact table that records the state of something at regular intervals, such as daily inventory or monthly account balances.Advanced
• Pessimistic Concurrency ControlA strategy that locks data when it is read for update, preventing conflicts by making others wait.Advanced
• Phantom ReadAn anomaly in which re-running a range query returns new or missing rows because another transaction inserted or deleted rows.Intermediate
• PhotonDatabricks' native vectorized query engine, written in C++, that accelerates Spark SQL and DataFrame workloads.Advanced
• Physical Data ModelThe implementation-specific model with actual tables, columns, data types, indexes, partitions and constraints for a chosen DBMS.Intermediate
• Pie ChartA circular chart divided into slices showing each category's proportion of a whole.Foundational
• Pipeline ExpectationsData quality constraints in Lakeflow Declarative Pipelines (DLT) that warn, drop invalid rows or fail the update when records violate them.Advanced
• PIVOT and UNPIVOTSQL operators that rotate data: PIVOT turns row values into columns, and UNPIVOT turns columns into rows.Intermediate
• PL/SQLOracle's procedural extension of SQL, used to write blocks, procedures, functions, packages and triggers.Intermediate
• Plan RegressionA performance drop caused by the optimizer switching a query to a worse execution plan.Advanced
• Point-in-Time Recovery (PITR)Restoring a database to its exact state at a specific moment, for example just before an accidental delete.Intermediate
• Poisson DistributionThe distribution of the count of events in a fixed interval of time or space, when events occur independently at a constant average rate λ.Intermediate
• Population and SampleThe population is the entire group of interest; a sample is the subset actually observed and measured.Foundational
• Power BI AppA packaged, read-only bundle of reports and dashboards from a workspace, distributed to a broad audience.Intermediate
• Power BI DashboardA single-page canvas in the Power BI Service made of tiles pinned from one or more reports, used for at-a-glance monitoring.Foundational
• Power BI DesktopMicrosoft's free Windows application for connecting to data, transforming it with Power Query, modeling it with DAX and designing reports.Foundational
• Power BI ServiceThe cloud SaaS component of Power BI (app.powerbi.com) for publishing, sharing, refreshing and collaborating on semantic models, reports, dashboards and apps.Foundational
• Power QueryMicrosoft's data connection and transformation engine, used in Power BI, Excel, Dataflows and Fabric, with a GUI that records steps as M code.Foundational
• Pre-Attentive AttributesVisual properties such as color, size, position, length and orientation that the brain processes almost instantly, before conscious attention.Intermediate
• Predictive AnalyticsAnalytics that answers 'what is likely to happen?' using statistical models and machine learning on historical data.Foundational
• Prescriptive AnalyticsAnalytics that answers 'what should we do?' by recommending actions using optimization, simulation and decision models.Intermediate
• Primary Key (PK)A column or set of columns whose values uniquely identify each row in a table; it cannot contain NULLs.Foundational
• Probability DistributionA function describing the likelihood of each possible value of a random variable.Foundational
• Property GraphA graph model in which nodes and relationships both carry labels and key-value properties.Advanced
• Q&A VisualA Power BI feature that lets users ask questions in natural language and get auto-generated visuals.Intermediate
• QUALIFY ClauseA clause in Snowflake, Databricks SQL, BigQuery and Teradata that filters rows on the result of window functions.Intermediate
• QuartileValues that split ordered data into four equal parts: Q1 (25th percentile), Q2 (the median) and Q3 (75th percentile).Foundational
• Query Acceleration Service (QAS)A Snowflake warehouse feature that offloads parts of eligible large scans and filters to shared serverless compute, helping outlier queries.Advanced
• Query Execution PlanThe sequence of physical operations (scans, seeks, joins, sorts) that the database chooses to run a query.Intermediate
• Query FoldingPower Query's ability to translate transformation steps into a single native source query, such as SQL, so the source does the work.Advanced
• Query OptimizerThe database component that evaluates possible ways to run a query and picks the lowest-cost plan.Intermediate
• Query ProfileSnowsight's graphical breakdown of a Snowflake query's execution plan, operator statistics, pruning and spilling.Intermediate
• Query StoreA SQL Server and Azure SQL feature that captures the history of queries, plans and runtime statistics for performance troubleshooting.Advanced
• RangeThe difference between the maximum and minimum values, the simplest measure of spread.Foundational
• RANK and DENSE_RANKRanking window functions: RANK gives tied rows the same rank and leaves gaps; DENSE_RANK gives ties the same rank without gaps.Intermediate
• Read CommittedAn isolation level in which a transaction sees only committed data, though values may change between reads.Intermediate
• Read Committed Snapshot Isolation (RCSI)A SQL Server and Azure SQL option that makes Read Committed use row versions, so readers do not block writers.Advanced
• Read UncommittedThe lowest isolation level, which takes no shared locks on reads and allows dirty reads.Intermediate
• Reader AccountA Snowflake account created and paid for by a data provider so consumers without their own Snowflake account can query shared data.Advanced
• Real-Time IntelligenceThe Fabric workload for ingesting, analyzing and acting on streaming data: Eventstream, Eventhouse/KQL databases, Real-Time Dashboards and Activator.Advanced
• Recovery ModelA SQL Server database setting (Simple, Full or Bulk-logged) that controls how the transaction log is kept and which restores are possible.Advanced
• Recursive CTEA CTE that references itself to traverse hierarchical or graph data such as org charts or bills of materials.Advanced
• RedisAn in-memory key-value data store supporting strings, hashes, lists, sets, sorted sets and streams, widely used for caching.Intermediate
• Reference DataStandardized code sets and classifications used to categorize other data, such as country codes, currency codes and status values.Foundational
• Referential IntegrityThe guarantee that every foreign key value matches an existing key in the referenced table, so no orphaned rows exist.Foundational
• RELATED FunctionA DAX function that fetches a value from the 'one' side of a relationship into the current row context on the 'many' side.Intermediate
• Relational DatabaseA database that stores data in tables of rows and columns, linked through keys, and queried with SQL.Foundational
• Relational Database Management System (RDBMS)Software that creates, manages and queries relational databases, enforcing schemas, constraints, security and transactions.Foundational
• Repartition and CoalesceSpark methods that change partition counts: repartition() fully shuffles to increase or rebalance; coalesce() merges partitions without a full shuffle.Advanced
• Repeatable ReadAn isolation level that guarantees rows read once will return the same values if read again in the same transaction.Advanced
• Replica SetA group of MongoDB servers holding the same data, with one primary for writes and secondaries that replicate and can take over automatically.Intermediate
• ResidualThe difference between an observed value and the value predicted by a model (y - ŷ).Intermediate
• Resilient Distributed Dataset (RDD)Spark's low-level, immutable, partitioned collection of objects that can be rebuilt from lineage after a failure.Intermediate
• Result CacheSnowflake's cloud-services cache of query results, reused for identical queries for 24 hours (extendable to 31 days) if the underlying data has not changed.Intermediate
• Reverse ETLSyncing modeled data from the warehouse back into operational tools such as CRM, marketing and support systems.Intermediate
• REVOKE StatementThe DCL statement that removes previously granted privileges from a user or role.Foundational
• RIGHT OUTER JOINA join that returns every row from the right table plus matching rows from the left, with NULLs where no match exists.Foundational
• Role-Playing DimensionA single physical dimension referenced several times by a fact table in different roles, such as Date as Order Date and Ship Date.Intermediate
• Roll-UpAggregating data to a higher, less detailed level of a hierarchy, such as City to Country; the opposite of drill-down.Foundational
• ROLLBACK StatementThe TCL command that undoes all uncommitted changes in the current transaction, or back to a savepoint.Foundational
• ROLLUP and CUBEGROUP BY extensions that add subtotal rows: ROLLUP for hierarchical subtotals and CUBE for every combination of the grouping columns.Advanced
• RowA single record in a table, holding one value (or NULL) for each column; called a tuple in relational theory.Foundational
• Row Access PolicyA Snowflake Enterprise object that filters which rows a query returns based on the user's role or a mapping table.Advanced
• Row ContextThe current row being evaluated in a DAX calculated column or iterator function such as SUMX or FILTER.Advanced
• Row-Level Security (RLS)Restricting which rows a user can see based on their identity or role, enforced by the data platform or semantic model.Intermediate
• ROW_NUMBER FunctionA window function that assigns a unique sequential integer to rows within each partition according to the ORDER BY.Intermediate
• Running TotalA cumulative sum that adds each row's value to the total of all preceding rows in a defined order.Foundational
• Sampling BiasSystematic error that occurs when some members of a population are more likely to be sampled than others, so the sample misrepresents the population.Foundational
• Sargable QueryA query whose predicates can use an index seek or pruning (Search ARGument ABLE), typically because columns are not wrapped in functions.Advanced
• SAVEPOINT (SQL)A named marker inside a transaction that allows a partial rollback to that point without abandoning the whole transaction.Intermediate
• Scaling PolicyThe multi-cluster warehouse setting (Standard or Economy) that controls how eagerly Snowflake starts additional clusters.Advanced
• Scatter PlotA chart that plots two numeric variables as points to reveal relationships, clusters and outliers.Foundational
• SCD Type 1A slowly changing dimension method that overwrites the old attribute value, keeping no history.Intermediate
• SCD Type 2A slowly changing dimension method that inserts a new row for each change, with effective dates and a current-row flag, preserving full history.Intermediate
• SCD Type 3A slowly changing dimension method that adds a column to store the previous value alongside the current one, keeping limited history.Advanced
• Scheduled RefreshAutomatically refreshing a Power BI semantic model's imported data at set times in the Service.Foundational
• Schema DriftUnplanned changes in a source's structure, such as new, removed or renamed columns or changed types, that can break pipelines.Intermediate
• Schema EvolutionChanging a table's or stream's schema over time, for example by adding columns, while keeping existing data and consumers working.Intermediate
• Schema-on-ReadApplying structure to data when it is queried, rather than enforcing a schema when it is written.Intermediate
• Schema-on-WriteValidating and structuring data to a predefined schema when it is loaded, rejecting non-conforming records.Intermediate
• Search Optimization ServiceA Snowflake Enterprise feature that builds a persistent search access path to speed selective point lookups, substring searches and VARIANT field searches.Advanced
• SeasonalityRegular, calendar-related patterns that repeat over fixed periods, such as daily, weekly or yearly cycles.Foundational
• Second Normal Form (2NF)A table is in 2NF when it is in 1NF and every non-key column depends on the whole primary key, not part of it.Intermediate
• Secure Data SharingSnowflake's capability to share live, read-only database objects with other accounts without copying or moving data.Intermediate
• Secure ViewA Snowflake view whose definition is hidden from unauthorized users and whose optimizations cannot expose underlying data.Intermediate
• SELECT StatementThe SQL statement that retrieves rows and columns from one or more tables or views.Foundational
• Selection BiasBias introduced when the way subjects or data are selected relates to the outcome being studied.Intermediate
• Self JoinA join of a table to itself, using two aliases, to compare rows within the same table.Intermediate
• Self-Service BIEnabling business users to create their own reports and analyses from governed data without relying on IT for each request.Foundational
• Semantic LayerA business-friendly abstraction over physical data that defines entities, relationships and metrics once for consistent use across tools.Intermediate
• Semantic ModelPower BI's model, formerly called a dataset, containing tables, relationships, measures, hierarchies and security that reports query.Intermediate
• Semi JoinA join pattern that returns rows from one table that have at least one match in another, without duplicating them.Advanced
• Semi-Additive MeasureA fact that can be summed across some dimensions but not across time, such as account balances or inventory levels.Advanced
• Semi-Structured DataData with self-describing tags or keys but no rigid tabular schema, such as JSON, XML, Avro or Parquet with nested fields.Foundational
• Separation of Storage and ComputeAn architecture in which data lives in independent storage and compute resources scale, start and stop separately.Intermediate
• SequenceA standalone database object that generates unique numbers on request, independent of any one table.Intermediate
• Sequential Color PaletteA single-hue (or light-to-dark) color scale for ordered numeric data running from low to high.Intermediate
• SerializableThe strictest isolation level, in which concurrent transactions behave as if they had run one after another.Advanced
• Session WindowA dynamic window per key that groups events separated by less than a gap of inactivity.Advanced
• Shard KeyThe field or fields used to decide which shard stores each document or row.Advanced
• ShardingHorizontal partitioning of data across multiple database servers (shards) to scale writes and storage.Intermediate
• Shared-Disk ArchitectureA distributed design in which all compute nodes access a common storage layer.Advanced
• Shared-Nothing ArchitectureA distributed design in which each node has its own CPU, memory and disk, sharing nothing with other nodes.Advanced
• ShuffleRedistributing data across Spark executors by key, involving disk and network I/O, to perform joins, aggregations or repartitioning.Advanced
• Significance Level (α)The threshold probability α for rejecting the null hypothesis, commonly 0.05, which equals the accepted Type I error rate.Foundational
• Silver LayerThe medallion layer that holds cleansed, deduplicated, validated and conformed data at roughly entity grain.Intermediate
• Simple Random Sampling (SRS)A sampling method in which every member of the population has an equal chance of being selected.Foundational
• Simpson's ParadoxA phenomenon in which a trend in several groups reverses or disappears when the groups are combined.Advanced
• Single Source of Truth (SSOT)The practice of having one authoritative source for each data element or metric so that everyone uses consistent numbers.Foundational
• SkewnessA measure of a distribution's asymmetry: right (positive) skew has a long right tail, left (negative) skew a long left tail.Intermediate
• Slice and DiceOLAP operations: slicing fixes one dimension to a single value, and dicing selects a sub-cube using values from several dimensions.Foundational
• SlicerAn on-canvas Power BI visual that lets users filter other visuals on the page by selecting values.Foundational
• Sliding Window (Stream Processing)Fixed-size windows that overlap because they advance by a smaller interval, so an event can fall into several windows.Advanced
• Slowly Changing Dimension (SCD)Techniques for handling changes to dimension attributes over time, such as a customer moving city.Intermediate
• Small File ProblemPerformance degradation caused by large numbers of tiny files, which increase metadata overhead and per-file open costs.Advanced
• Small MultiplesA grid of small charts with the same scale and axes, each showing a different subset of the data, for easy comparison.Intermediate
• Snapshot IsolationAn isolation level in which each transaction reads a consistent snapshot of the data as of its start, using row versions.Advanced
• Snowflake ArchitectureSnowflake's three independent layers: database storage, query processing (virtual warehouses) and cloud services.Foundational
• Snowflake CreditThe unit of Snowflake compute consumption, charged for warehouses, serverless features and cloud services above the daily threshold.Foundational
• Snowflake EditionsSnowflake service tiers (Standard, Enterprise, Business Critical, Virtual Private Snowflake) that unlock progressively more features and security.Foundational
• Snowflake Fail-safeA non-configurable 7-day period after Time Travel during which Snowflake can recover permanent table data for disaster recovery.Intermediate
• Snowflake Iceberg TableA Snowflake table that stores data and metadata in the Apache Iceberg format in customer-managed cloud storage, using Snowflake or an external catalog.Advanced
• Snowflake MarketplaceSnowflake's marketplace of free and paid listings of live datasets, data services and Native Apps from third-party providers.Intermediate
• Snowflake Replication and FailoverFeatures that replicate Snowflake databases and account objects to other regions or clouds, with failover groups and client redirect for continuity.Advanced
• Snowflake Resource MonitorA Snowflake object that tracks credit usage by warehouses against a quota and can notify, suspend, or suspend immediately at thresholds.Intermediate
• Snowflake SchemaA dimensional model whose dimension tables are normalized into multiple related tables, such as Product to Subcategory to Category.Intermediate
• Snowflake StageA named or implicit location of data files used for loading and unloading: internal (Snowflake-managed) or external (S3, Azure Blob, GCS).Intermediate
• Snowflake StreamA Snowflake object that records DML changes (inserts, updates, deletes) to a table since an offset, enabling CDC processing.Intermediate
• Snowflake System-Defined RolesSnowflake's built-in roles: ORGADMIN, ACCOUNTADMIN, SECURITYADMIN, USERADMIN, SYSADMIN and PUBLIC.Intermediate
• Snowflake TaskA Snowflake object that runs a SQL statement, procedure call or Snowflake Scripting block on a schedule or after a predecessor task, forming DAGs.Intermediate
• SnowparkSnowflake's developer framework with Python, Java and Scala DataFrame APIs whose operations are pushed down and executed inside Snowflake.Intermediate
• SnowpipeSnowflake's serverless continuous ingestion service that loads staged files soon after arrival, triggered by cloud event notifications or REST calls.Intermediate
• Snowpipe StreamingA Snowflake API for low-latency, row-level ingestion of streaming data directly into tables without staging files.Advanced
• SnowsightSnowflake's web interface for worksheets, notebooks, dashboards, data browsing, administration and monitoring.Foundational
• SnowSQLSnowflake's legacy command-line client for executing SQL and PUT/GET file transfers; the newer Snowflake CLI is its successor.Intermediate
• Spark ActionA Spark operation that triggers execution and returns a result to the driver or writes output, such as count, collect, show, take or write.Intermediate
• Spark CachingPersisting a DataFrame in memory and/or disk with cache() or persist() so that repeated actions reuse it instead of recomputing.Intermediate
• Spark DataFrameA distributed collection of rows organized into named, typed columns, optimized by Spark's Catalyst optimizer.Intermediate
• Spark DriverThe Spark process that runs the main program, builds the DAG, schedules tasks and collects results.Intermediate
• Spark ExecutorA JVM process on a worker node that runs Spark tasks and stores cached data for an application.Intermediate
• Spark StageA set of Spark tasks that can run without a shuffle; a job is split into stages at shuffle boundaries.Advanced
• Spark TransformationA lazy Spark operation that defines a new DataFrame from an existing one, such as select, filter, withColumn, join or groupBy.Intermediate
• SparklineA small, word-sized line chart without axes that shows the trend shape alongside a number or in a table.Intermediate
• Spearman Rank Correlation (ρ)A nonparametric correlation computed on ranks, measuring the strength of a monotonic relationship.Advanced
• SpillingWriting intermediate query data to local disk, or remote cloud storage, when warehouse or executor memory is insufficient.Advanced
• SQL Analytics EndpointA read-only T-SQL interface automatically created for each Fabric lakehouse (and mirrored database) to query its Delta tables.Advanced
• SQL Data TypesThe categories of values a column can hold: numeric (INT, DECIMAL, FLOAT), character (CHAR, VARCHAR), date/time, Boolean, binary and semi-structured.Foundational
• SQL Logical Query Processing OrderThe order in which SQL logically evaluates clauses: FROM/JOIN, WHERE, GROUP BY, HAVING, SELECT, DISTINCT, ORDER BY, then LIMIT/TOP.Intermediate
• Stacked Bar ChartA bar chart in which each bar is divided into segments showing the parts that make up the total.Foundational
• Staging Area (Data Warehousing)An intermediate storage location where extracted data lands before being cleansed, transformed and loaded into target tables.Foundational
• Standard Deviation (SD)The square root of variance, describing typical distance from the mean in the data's own units.Foundational
• Standard Error (SE)The standard deviation of a sampling distribution, usually of the mean: SE = s / √n.Intermediate
• Star SchemaA dimensional model with a central fact table joined directly to denormalized dimension tables, forming a star shape.Foundational
• Statistical PowerThe probability that a test correctly rejects a false null hypothesis (1 - β); 80% is a common target.Advanced
• Stored ProcedureA named, precompiled set of SQL (and procedural) statements stored in the database and executed with CALL or EXEC.Intermediate
• Stream ProcessingContinuously processing data records as they arrive to produce near-real-time results.Intermediate
• Streamlit in SnowflakeA feature for building and hosting interactive Python Streamlit data apps directly inside Snowflake, governed by Snowflake roles.Intermediate
• Strong ConsistencyA guarantee that every read returns the most recent committed write, as if there were a single copy of the data.Intermediate
• Structured DataData organized into a fixed schema of rows and columns, such as relational tables or spreadsheets.Foundational
• Structured Query Language (SQL)The standard declarative language for defining, querying and manipulating data in relational databases.Foundational
• Structured StreamingSpark's stream processing engine, which treats a stream as an unbounded table and processes it incrementally with the DataFrame API.Intermediate
• Student's t-TestA test comparing means (one sample against a value, or two independent groups) when the population standard deviation is unknown, using the t-distribution.Intermediate
• SubqueryA query nested inside another statement, used as a value, a list, or a derived table.Foundational
• SuperkeyAny set of one or more columns whose combined values uniquely identify each row, whether or not it is minimal.Advanced
• Surrogate KeyA system-generated identifier with no business meaning, such as an auto-increment integer or GUID, used as a primary key.Intermediate
• Survivorship BiasDrawing conclusions only from entities that 'survived' a selection process while ignoring those that failed or dropped out.Intermediate
• Synchronous ReplicationReplication in which a write is acknowledged only after it is committed on both the primary and the replica.Intermediate
• Systematic SamplingSelecting every kth item from an ordered list after a random start.Intermediate
• Table AliasA short temporary name for a table in a query, used to qualify columns and required for self joins.Foundational
• Table CalculationA Tableau calculation computed on the aggregated results in the view, such as running total, percent of total, rank, difference or moving average.Intermediate
• Table PartitioningDividing a large table into smaller physical pieces by a key such as date, while queries still see a single table.Intermediate
• Tableau BridgeA Tableau client that connects Tableau Cloud to data behind a private network for live queries and extract refreshes.Advanced
• Tableau CloudTableau's fully hosted SaaS analytics platform, formerly Tableau Online, managed by Salesforce.Intermediate
• Tableau DesktopSalesforce's authoring application for connecting to data and building interactive worksheets, dashboards and stories.Foundational
• Tableau ExtractA compressed snapshot of data saved in Tableau's .hyper format for fast performance and offline use.Intermediate
• Tableau GroupA Tableau field that combines dimension members into higher-level categories, such as grouping misspellings or regions.Foundational
• Tableau Order of OperationsTableau's filter and calculation sequence: extract, data source, context, Top N/FIXED, dimension, INCLUDE/EXCLUDE, measure, then table calc filters.Advanced
• Tableau ParameterA user-controlled workbook variable (number, date, string or list) that can be referenced in calculations, filters, reference lines and bins.Intermediate
• Tableau PermissionsCapabilities (View, Filter, Download, Web Edit and others) granted or denied to users and groups on projects, workbooks, views and data sources.Advanced
• Tableau Prep BuilderTableau's visual data preparation tool for cleaning, shaping, joining, unioning, pivoting and aggregating data in flows.Intermediate
• Tableau ProjectA folder-like container in a Tableau site that organizes content and carries permission rules.Advanced
• Tableau PulseA Tableau Cloud feature that delivers personalized, AI-generated metric insights and digests to users in Slack, email and mobile.Advanced
• Tableau RelationshipsTableau's logical-layer links between tables that defer join type and level of detail until analysis time ('noodles').Intermediate
• Tableau ServerTableau's self-hosted platform for publishing, sharing, governing and refreshing workbooks and data sources.Intermediate
• Tableau Services Manager (TSM)The web UI and command-line tool for installing, configuring, scaling, backing up and maintaining Tableau Server.Advanced
• Tableau SetA custom field defining a subset of dimension members, IN or OUT, based on selection, a condition or Top N.Intermediate
• Tableau SiteAn isolated tenant on Tableau Server or Tableau Cloud with its own users, groups, projects and content.Advanced
• Tableau StoryA sequence of Tableau sheets or dashboards (story points) arranged to walk an audience through a narrative.Foundational
• Temporary TableA table that exists only for the duration of the user's session and is visible only to that session.Intermediate
• Third Normal Form (3NF)A table is in 3NF when it is in 2NF and no non-key column depends on another non-key column (no transitive dependencies).Intermediate
• Three-Level NamespaceAddressing tables as catalog.schema.table in Unity Catalog, or database.schema.object in Snowflake.Intermediate
• Three-Valued Logic (3VL)SQL's logic system, in which conditions evaluate to TRUE, FALSE or UNKNOWN because of NULLs.Advanced
• Tidy DataHadley Wickham's data structure principle: each variable is a column, each observation is a row and each type of observational unit is a table.Intermediate
• Time Intelligence FunctionsDAX functions such as TOTALYTD, SAMEPERIODLASTYEAR, DATEADD, DATESYTD and PARALLELPERIOD that compute values across periods.Advanced
• Time SeriesA sequence of observations recorded at successive points in time, often at regular intervals.Intermediate
• Time Series DecompositionSeparating a time series into trend, seasonal and residual (irregular) components, additively or multiplicatively.Advanced
• Time TravelA Snowflake feature for querying, cloning or restoring data as it existed at any point within a retention period.Intermediate
• Time-Series Database (TSDB)A database optimized for timestamped measurements, offering fast ingestion, time-based compression, retention and windowed aggregation.Intermediate
• Top-N QueryA query that returns the N highest or lowest rows overall or per group.Intermediate
• Transact-SQLMicrosoft's SQL dialect for SQL Server, Azure SQL, Synapse and Fabric Warehouse, with procedural extensions.Foundational
• Transaction Control Language (TCL)The SQL commands that manage transactions: BEGIN/START TRANSACTION, COMMIT, ROLLBACK and SAVEPOINT.Foundational
• Transaction Fact TableA fact table with one row per discrete event at the most atomic grain, such as each sale or each click.Intermediate
• Transaction Isolation LevelA setting that defines which concurrency anomalies a transaction may see: Read Uncommitted, Read Committed, Repeatable Read or Serializable.Intermediate
• Transaction LogA sequential record of every change made by transactions, used for recovery, rollback and replication.Intermediate
• Transaction Log BackupA backup of the transaction log records since the last log backup, enabling point-in-time recovery and freeing log space.Advanced
• Transient TableA Snowflake table that persists until dropped but has no Fail-safe and at most 1 day of Time Travel, which lowers storage cost.Intermediate
• Transitive DependencyAn indirect dependency in which a non-key attribute depends on another non-key attribute rather than directly on the key.Intermediate
• TreemapA chart that displays hierarchical part-to-whole data as nested rectangles sized by value.Intermediate
• Tri-Secret SecureA Business Critical feature that combines a Snowflake-maintained key and a customer-managed key in the cloud KMS into a composite master key.Advanced
• TriggerProcedural code that runs automatically in response to INSERT, UPDATE or DELETE events (or DDL events) on a table.Intermediate
• TRUNCATE StatementA statement that quickly removes all rows from a table while keeping its structure, typically with minimal logging.Intermediate
• Truncated AxisA y-axis that does not start at zero, exaggerating differences; misleading for bar charts but sometimes acceptable for line charts if clearly labeled.Foundational
• TRY_CAST FunctionA conversion function that returns NULL instead of raising an error when the value cannot be converted.Intermediate
• Tumbling WindowFixed-size, non-overlapping, contiguous time windows; each event belongs to exactly one window.Advanced
• Tunable ConsistencyThe ability to choose, per operation or per account, how many replicas must acknowledge a read or write.Advanced
• Two-Phase Commit (2PC)A protocol that coordinates a distributed transaction: participants first vote to prepare, then all commit or all abort.Advanced
• Two-Tailed TestA hypothesis test in which the alternative is non-directional (≠), splitting α across both tails of the distribution.Intermediate
• Type I ErrorRejecting a true null hypothesis: a false positive, with probability α.Intermediate
• Type II ErrorFailing to reject a false null hypothesis: a false negative, with probability β.Intermediate
• UNDROPA Snowflake command that restores a dropped table, schema or database within its Time Travel retention period.Intermediate
• UNION ALLA set operator that stacks the results of two queries and keeps all rows, including duplicates.Foundational
• UNION OperatorA set operator that combines the results of two queries into one set and removes duplicate rows.Foundational
• Unique ConstraintA constraint that prevents duplicate values in a column or column combination.Foundational
• Unity Catalog (UC)Databricks' unified governance layer for data and AI assets, providing centralized access control, auditing, lineage and discovery across workspaces.Intermediate
• Unpivot ColumnsA Power Query transformation that turns selected columns into attribute-value row pairs, converting wide data to long format.Intermediate
• Unstructured DataData with no predefined model, such as documents, emails, images, audio and video.Foundational
• UPDATE StatementThe DML statement that modifies existing column values in rows that match a condition.Foundational
• User-Defined Function (UDF)A custom function created in the database that returns a scalar value or a table and can be called inside SQL statements.Intermediate
• User-Defined Table Function (UDTF)A function that returns zero or more rows (a table) for each input, used in the FROM clause.Advanced
• USERELATIONSHIP FunctionA DAX modifier used in CALCULATE that activates an inactive relationship for one calculation.Advanced
• VACUUM CommandA Delta Lake command that permanently deletes data files no longer referenced by the table and older than the retention threshold (7 days by default).Advanced
• VarianceThe average squared deviation from the mean, measuring how spread out data are; units are the square of the data's units.Intermediate
• VARIANT Data TypeA Snowflake data type that stores semi-structured data such as JSON, Avro, ORC, Parquet or XML, with a maximum size of 128 MB per value.Intermediate
• vCore Purchasing ModelAn Azure SQL pricing model in which you choose virtual cores, memory and storage independently, with General Purpose, Business Critical and Hyperscale tiers.Intermediate
• Vertical PartitioningSplitting a table by columns into separate tables that share the primary key.Intermediate
• VertiPaqThe in-memory columnar storage engine behind Power BI Import mode, Analysis Services Tabular and Power Pivot.Advanced
• ViewA named stored query that behaves like a virtual table; it stores no data and runs its query when referenced.Foundational
• Virtual WarehouseA named cluster of Snowflake compute resources that executes queries and DML; it can be started, stopped and resized independently.Foundational
• Warehouse CacheThe local SSD cache in a running Snowflake warehouse that keeps recently read table data to speed later queries.Intermediate
• Warehouse SizeThe T-shirt size of a Snowflake virtual warehouse (XS, S, M, L, XL up to 6XL), where each step doubles compute and credit consumption.Intermediate
• Waterfall ChartA chart showing how an initial value is increased and decreased by sequential positive and negative contributions to reach a final value.Intermediate
• Watermark (Streaming)A threshold in stream processing that estimates how far event time has progressed, determining when windows can close and how late data is handled.Advanced
• Weighted AverageAn average in which each value is multiplied by a weight reflecting its importance or frequency, divided by the sum of the weights.Foundational
• WHERE ClauseThe clause that filters individual rows before grouping, keeping only those where the condition is true.Foundational
• Wide TransformationA Spark transformation in which output partitions depend on data from many input partitions, requiring a shuffle.Advanced
• Wide vs Long DataTwo layouts for the same data: wide has one column per variable value (such as per month); long (tidy) has one row per observation.Intermediate
• Wide-Column StoreA NoSQL database that organizes data into rows with dynamic columns grouped into column families, built for massive write throughput.Intermediate
• Window FrameThe subset of rows within a partition that a window function considers, set with ROWS or RANGE BETWEEN.Advanced
• Window FunctionA function that computes a value across a set of rows related to the current row, defined with OVER(), without collapsing them.Intermediate
• WindowingGrouping unbounded streaming data into finite time-based buckets for aggregation.Advanced
• Workspace RolesPower BI and Fabric workspace permission levels: Admin, Member, Contributor and Viewer.Intermediate
• Write-Ahead Logging (WAL)A technique in which changes are recorded in a durable log before being applied to data files.Advanced
• Z-OrderingA Delta Lake technique that co-locates related values across files using a space-filling curve, improving data skipping on frequently filtered columns.Advanced
• Z-ScoreThe number of standard deviations a value lies from the mean: z = (x - μ) / σ.Intermediate
• Z-TestA hypothesis test using the standard normal distribution, appropriate when the population SD is known or samples are large, including tests of proportions.Intermediate
• Zero-Copy CloningCreating an instant copy of a Snowflake database, schema or table that shares the original micro-partitions until either side changes.Intermediate