Microsoft Fabric Analytics Engineer Associate: key terms

Flashcards for this exam Microsoft Fabric Analytics Engineer Associate guide

• 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
• Active RelationshipThe single relationship between two Power BI tables that propagates filters by default; additional relationships are inactive.Intermediate
• Additive MeasureA fact that can be summed meaningfully across every dimension, such as sales amount or quantity.Intermediate
• ALL FunctionA DAX function that returns all rows of a table or column, ignoring filters; inside CALCULATE it removes filters (like REMOVEFILTERS).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
• Bridge TableA table that resolves a many-to-many relationship between a fact and a dimension, or handles multivalued dimensions.Advanced
• Bronze LayerThe raw landing layer of a medallion architecture, holding source data as ingested, often append-only with load metadata.Intermediate
• Bus MatrixA Kimball planning grid that lists business processes (rows) against conformed dimensions (columns) to design an integrated warehouse.Advanced
• 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 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
• 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
• Chasm TrapAn error that occurs when two fact tables are joined through a shared dimension, multiplying rows and overstating measures from both.Advanced
• 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
• Columnstore IndexA SQL Server and Azure SQL index that stores data column by column in compressed segments for fast analytic scans.Advanced
• Composite ModelA Power BI model that combines storage modes, such as Import and DirectQuery tables, or that chains to other published semantic models.Advanced
• Conformed DimensionA dimension shared with consistent keys, attributes and meaning across multiple fact tables or data marts.Intermediate
• Context TransitionThe DAX behavior in which CALCULATE, or a measure reference, converts the current row context into an equivalent filter context.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
• Cross-Filter DirectionThe direction in which a Power BI relationship propagates filters: single (one side to many side) or both (bidirectional).Advanced
• 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 CatalogAn inventory of an organization's data assets with metadata, descriptions, ownership, classifications, lineage and search for discovery.Intermediate
• Data CleansingDetecting and correcting or removing inaccurate, incomplete, duplicate or improperly formatted data.Foundational
• 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 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 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 OrchestrationCoordinating the scheduling, dependencies, retries and monitoring of data pipeline tasks.Intermediate
• Data PipelineAn automated series of steps that moves data from sources through transformations to destinations.Foundational
• Data ProfilingExamining data to summarize its structure, content, completeness, distributions, patterns and anomalies before using it.Foundational
• Data VirtualizationQuerying data in place across multiple sources through a unified layer, without physically copying it.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
• 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
• Degenerate DimensionA dimension key, such as an order or invoice number, stored in the fact table with no separate dimension table.Advanced
• Delta LakeAn open-source table format that adds ACID transactions, schema enforcement and evolution, time travel and MERGE to Parquet files.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
• 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
• 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
• DirectQueryA Power BI storage mode that sends queries to the source at report time instead of importing data, keeping results current.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
• 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
• EndorsementPower BI and Fabric badges (Promoted, Certified and Master data) that signal trustworthy content to users.Intermediate
• 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
• 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
• Fan TrapA modeling or join error in which joining tables at different grains duplicates rows and inflates aggregated totals.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
• 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
• 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
• 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
• Import ModeA Power BI storage mode that loads compressed data into the in-memory VertiPaq engine for the fastest query performance.Foundational
• 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
• 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
• Junk DimensionA dimension that combines miscellaneous low-cardinality flags and indicators into one table to avoid cluttering the fact table.Advanced
• Kimball MethodologyRalph Kimball's bottom-up approach that builds a data warehouse from dimensional star schemas linked by conformed dimensions.Intermediate
• 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
• 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
• Medallion ArchitectureA lakehouse design pattern that refines data progressively through Bronze (raw), Silver (cleansed) and Gold (business-ready) layers.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
• Non-Additive MeasureA fact that cannot be summed across any dimension, such as percentages, ratios or unit prices.Intermediate
• Object-Level Security (OLS)Power BI semantic model security that hides entire tables or columns from specified roles.Advanced
• 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
• 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
• 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
• 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
• Periodic Snapshot Fact TableA fact table that records the state of something at regular intervals, such as daily inventory or monthly account balances.Advanced
• 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
• 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
• Real-Time IntelligenceThe Fabric workload for ingesting, analyzing and acting on streaming data: Eventstream, Eventhouse/KQL databases, Real-Time Dashboards and Activator.Advanced
• 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
• 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
• 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
• 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
• Schema DriftUnplanned changes in a source's structure, such as new, removed or renamed columns or changed types, that can break pipelines.Intermediate
• 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-Additive MeasureA fact that can be summed across some dimensions but not across time, such as account balances or inventory levels.Advanced
• Separation of Storage and ComputeAn architecture in which data lives in independent storage and compute resources scale, start and stop separately.Intermediate
• Session WindowA dynamic window per key that groups events separated by less than a gap of inactivity.Advanced
• Silver LayerThe medallion layer that holds cleansed, deduplicated, validated and conformed data at roughly entity grain.Intermediate
• 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
• Snowflake SchemaA dimensional model whose dimension tables are normalized into multiple related tables, such as Product to Subcategory to Category.Intermediate
• Spark DataFrameA distributed collection of rows organized into named, typed columns, optimized by Spark's Catalyst optimizer.Intermediate
• SQL Analytics EndpointA read-only T-SQL interface automatically created for each Fabric lakehouse (and mirrored database) to query its Delta tables.Advanced
• Star SchemaA dimensional model with a central fact table joined directly to denormalized dimension tables, forming a star shape.Foundational
• Stream ProcessingContinuously processing data records as they arrive to produce near-real-time results.Intermediate
• Surrogate KeyA system-generated identifier with no business meaning, such as an auto-increment integer or GUID, used as a primary key.Intermediate
• Time Intelligence FunctionsDAX functions such as TOTALYTD, SAMEPERIODLASTYEAR, DATEADD, DATESYTD and PARALLELPERIOD that compute values across periods.Advanced
• Transact-SQLMicrosoft's SQL dialect for SQL Server, Azure SQL, Synapse and Fabric Warehouse, with procedural extensions.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
• Tumbling WindowFixed-size, non-overlapping, contiguous time windows; each event belongs to exactly one window.Advanced
• USERELATIONSHIP FunctionA DAX modifier used in CALCULATE that activates an inactive relationship for one calculation.Advanced
• VertiPaqThe in-memory columnar storage engine behind Power BI Import mode, Analysis Services Tabular and Power Pivot.Advanced
• 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