CompTIA Data+ (DA0-001) glossary
Terms selected for CompTIA Data+ (DA0-001) based on common objective language and practice focus.
Bar Chart
Visualization that compares categorical values using rectangular bars.
Read full term ->Categorical Data
Data represented by labels or categories rather than numeric magnitude.
Read full term ->Foreign Key
Field linking records across related tables.
Read full term ->Histogram
Chart showing frequency distribution of numeric values by bins.
Read full term ->JSON
Lightweight structured data format commonly used in APIs and data exchange.
Read full term ->Pie Chart
Circular chart representing category proportions as slices.
Read full term ->Primary Key
Unique identifier field for records in a relational table.
Read full term ->Scatter Plot
Chart showing relationship between two numeric variables.
Read full term ->Schema
Defined structure and organization of data fields and relationships.
Read full term ->SQL Query
Structured request for reading or manipulating relational data.
Read full term ->XML
Markup-based structured data format used in integration workflows.
Read full term ->Anomaly Detection
Technique used to identify values or behaviors that deviate from normal patterns.
Read full term ->Aggregated Data
Data combined from multiple records into summary-level values.
Read full term ->API Ingestion
Collecting data from application programming interfaces into analysis pipelines.
Read full term ->Bias in Data
Systematic distortion in datasets that can lead to inaccurate conclusions.
Read full term ->Confidence Interval
Estimated value range likely to contain a true population parameter.
Read full term ->Correlation
Statistical relationship showing how two variables move together.
Read full term ->Data Cleansing
Process of correcting errors and inconsistencies in raw data.
Read full term ->Data Governance
Policies and controls ensuring data quality, security, and proper usage.
Read full term ->Data Lake
Repository for storing structured and unstructured data at scale.
Read full term ->Data Mart
Subject-oriented subset of data warehouse tailored for specific teams.
Read full term ->Data Profiling
Assessing data quality, completeness, and distribution characteristics.
Read full term ->Data Warehouse
Centralized analytical store optimized for reporting and historical analysis.
Read full term ->Descriptive Statistics
Methods that summarize and describe key characteristics of datasets.
Read full term ->Dimension Table
Table storing descriptive attributes used for filtering and grouping facts.
Read full term ->ETL
Extract, Transform, Load pipeline for moving and preparing data.
Read full term ->ELT
Extract, Load, Transform pattern where transformation occurs in target platform.
Read full term ->Fact Table
Table containing measurable events linked to dimensions.
Read full term ->Imputation
Technique for filling missing data values using derived estimates.
Read full term ->Inferential Statistics
Methods used to draw conclusions about populations from samples.
Read full term ->KPI
Key performance indicator used to measure progress toward goals.
Read full term ->Data Normalization
Structuring data to reduce redundancy and improve consistency.
Read full term ->Null Value
Marker indicating missing or unknown data in a field.
Read full term ->Outlier
Data point significantly distant from typical values in a dataset.
Read full term ->Percentile
Value below which a given percentage of observations falls.
Read full term ->Regression Analysis
Statistical method for modeling relationships between variables.
Read full term ->Standard Deviation
Statistic measuring how spread out data points are from the mean.
Read full term ->Trend Analysis
Review of patterns over time to identify direction and momentum.
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