Google Data Analytics Professional Certificate: key terms

Flashcards for this exam Google Data Analytics Professional Certificate guide

• Aggregate FunctionA function that computes one value from a set of rows, such as SUM, AVG, COUNT, MIN, MAX, STDDEV or LISTAGG.Foundational
• Bar ChartA chart that compares values across categories using rectangular bars whose lengths are proportional to the values.Foundational
• 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
• Business Intelligence (BI)The technologies and practices for collecting, integrating, analyzing and presenting business data to support decision-making.Foundational
• CASE ExpressionSQL's conditional expression, which returns a value based on the first WHEN condition that is true.Foundational
• Categorical DataQualitative data that place observations into groups (nominal or ordinal) rather than measuring quantities.Foundational
• 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
• 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
• 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
• 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
• 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
• Data Analysis ProcessA structured analytics workflow; the Google Data Analytics certificate's six phases are Ask, Prepare, Process, Analyze, Share and Act.Foundational
• 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 LiteracyThe ability to read, work with, analyze and communicate with data.Foundational
• Data ParsingBreaking a string or semi-structured value into components, such as splitting a full address into street, city and postal code.Foundational
• Data ProfilingExamining data to summarize its structure, content, completeness, distributions, patterns and anomalies before using it.Foundational
• 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 StorytellingCommunicating insights by combining data, visuals and narrative tailored to an audience to drive understanding and action.Foundational
• Data TransformationConverting data from one structure, format or value set to another, by filtering, joining, aggregating, pivoting, deriving or recoding.Foundational
• Data VisualizationRepresenting data graphically so that patterns, trends, comparisons and outliers can be understood quickly.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 TableThe core relational storage object: a named set of rows sharing the same columns; formally called a relation.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
• 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
• 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
• Drill-DownNavigating from summarized data to a more detailed level along a hierarchy, such as Year to Quarter to Month.Foundational
• Duplicate Record DetectionIdentifying records that represent the same entity, through exact key matches or fuzzy matching of attributes.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
• Foreign Key (FK)A column in one table that references the primary or unique key of another table, enforcing a relationship between them.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
• Funnel AnalysisMeasuring how users progress through sequential steps toward a goal and where they drop off.Intermediate
• GROUP BY ClauseThe clause that groups rows sharing the same values so that aggregate functions return one row per group.Foundational
• HAVING ClauseThe clause that filters groups after GROUP BY, typically using aggregate conditions.Foundational
• IN OperatorA predicate that tests whether a value matches any value in a list or subquery.Foundational
• INNER JOINA join that returns only rows with matching values in both tables.Foundational
• KPI CardA visual that displays a key metric's current value, often against a target and with trend or status indicators.Foundational
• 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
• 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
• 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
• 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
• MedianThe middle value of ordered data, or the average of the two middle values when the count is even.Foundational
• 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
• NULLA marker meaning a value is missing or unknown; it is not zero, an empty string or false.Foundational
• Online Transaction Processing (OLTP)Systems that handle many short, concurrent read and write transactions, such as orders, payments and bookings.Foundational
• ORDER BY ClauseThe clause that sorts the final result set by one or more expressions, ascending (default) or descending.Foundational
• OutlierAn observation that lies unusually far from the other values in a dataset.Foundational
• PercentileThe value below which a given percentage of observations fall; the 90th percentile exceeds 90% of the values.Foundational
• Pie ChartA circular chart divided into slices showing each category's proportion of a whole.Foundational
• Population and SampleThe population is the entire group of interest; a sample is the subset actually observed and measured.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
• Primary Key (PK)A column or set of columns whose values uniquely identify each row in a table; it cannot contain NULLs.Foundational
• QuartileValues that split ordered data into four equal parts: Q1 (25th percentile), Q2 (the median) and Q3 (75th percentile).Foundational
• RangeThe difference between the maximum and minimum values, the simplest measure of spread.Foundational
• Relational DatabaseA database that stores data in tables of rows and columns, linked through keys, and queried with SQL.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
• RowA single record in a table, holding one value (or NULL) for each column; called a tuple in relational theory.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
• Scatter PlotA chart that plots two numeric variables as points to reveal relationships, clusters and outliers.Foundational
• SELECT StatementThe SQL statement that retrieves rows and columns from one or more tables or views.Foundational
• Standard Deviation (SD)The square root of variance, describing typical distance from the mean in the data's own units.Foundational
• 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
• Survivorship BiasDrawing conclusions only from entities that 'survived' a selection process while ignoring those that failed or dropped out.Intermediate
• Table AliasA short temporary name for a table in a query, used to qualify columns and required for self joins.Foundational
• 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
• 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
• UNION OperatorA set operator that combines the results of two queries into one set and removes duplicate rows.Foundational
• 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 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