CDMP flashcards

32 cards. Read the term and the definition here. The deck at the top of this page is optional.

Data governance definition

The exercise of authority and control over data management through policy, standards, decision rights, and accountability, ensuring data is managed as an asset and complies with obligations.

Data steward role

A domain expert accountable for data definitions, quality rules, and issue resolution within a subject area, working under data owners and often part-time.

Decision rights

The formally assigned authority to make specific data decisions, such as approving definitions, access grants, or quality thresholds, preventing unclear ownership and stalled issues.

Data policy vs standard

A policy states mandatory principles and rules; a standard specifies measurable requirements that implement the policy, while procedures describe how to comply.

Data governance maturity

A staged assessment of governance capability from ad hoc to defined, managed, measured, and optimized, requiring documented processes and assigned accountability at each level.

Conceptual data model

A technology-neutral model of business entities and their relationships, used to communicate scope and meaning with business stakeholders before logical and physical design.

Third normal form

A relational design state where no non-key attribute depends transitively on another non-key attribute, eliminating redundancy that causes update anomalies.

Star schema

A dimensional design with a central fact table joined to denormalized dimension tables, optimizing analytical query performance and business usability.

Slowly changing dimension Type 2

A dimension design that preserves full history by inserting a new row with version or effective dates when an attribute changes, keeping prior versions for point-in-time reporting.

Surrogate key

A system-generated, stable identifier independent of business meaning, used in facts and dimensions to insulate the model from changes in natural business keys.

Fact table grain

The precise business meaning of one row in a fact table, declared before selecting dimensions and measures, ensuring every measure is additive at that level.

Business metadata

Metadata describing business definitions, owners, rules, and glossary terms, enabling users to understand and trust data without technical schema knowledge.

Technical metadata

Metadata describing physical structures, data types, schemas, ETL mappings, and lineage, used by engineers to build, operate, and troubleshoot data pipelines.

Data lineage

The recorded path of data from source to target, including transformations, supporting impact analysis when objects change and root-cause tracing when defects appear.

Business glossary

A governed vocabulary of business terms with definitions, synonyms, owners, and rules, linked to technical metadata so users and systems share consistent meaning.

Data catalog

A searchable user interface over a metadata repository that helps users find data assets, view lineage and definitions, and assess fitness for use.

Data quality dimensions

Measurable aspects of data fitness including completeness, accuracy, consistency, timeliness, uniqueness, validity, and conformity, each requiring an operational definition and measurement method.

Data profiling

The statistical analysis of data columns, such as null rates, distinct counts, ranges, and pattern frequencies, used to discover quality issues before defining rules.

Completeness metric

The ratio of non-null or non-missing values to total values for an attribute, commonly expressed as a percentage and tracked against a defined threshold.

Data cleansing

The process of standardizing, parsing, matching, enriching, and correcting data to meet quality rules, ideally paired with root-cause remediation to prevent recurrence.

Data quality rule types

Categories of validation including completeness, validity, range, pattern, referential integrity, uniqueness, and cross-field consistency, each implemented as an automated check.

Data warehouse definition

A subject-oriented, integrated, time-variant, nonvolatile data store built from operational sources to support management reporting and analytical decision-making.

Conformed dimension

A dimension table with identical structure and content shared across multiple fact tables or data marts, enabling consistent drill-across reporting.

ETL versus ELT

ETL transforms data before loading it into the target warehouse; ELT loads raw data first and transforms inside the target platform, common in cloud data warehouses.

Dependent data mart

A data mart whose data is sourced from the enterprise data warehouse rather than directly from operational systems, reducing inconsistent definitions across marts.

OLAP drill-down

An operation that navigates from a summarized level of a dimension hierarchy to a more detailed level, increasing granularity for analysis.

Reference data

Controlled, relatively static code sets used to classify or categorize other data, such as country codes or status codes, shared across systems and requiring governed change control.

Master data

Core business entities such as customer, product, employee, supplier, and location that are shared across processes and require a single trusted version.

Golden record

The single trusted version of a master entity, produced by survivorship rules that select or merge attribute values from multiple source systems.

MDM registry style

A master data management approach that indexes and links source records without creating a central golden record, leaving source systems authoritative.

Entity resolution

The process of identifying records that refer to the same real-world entity using deterministic keys or probabilistic similarity scoring with tuned thresholds.

Change data capture

A data integration technique that identifies inserts, updates, and deletes since the last run using timestamps, log-based capture, or triggers to move only changed data.