ISC Area I.B — Data Management Fundamentals for CPAs

Data governance

The set of decision rights, policies, roles, and procedures that determine how an organization’s data is created, used, protected, and retired.

Data owner

Typically a business executive accountable for a dataset who authorizes access and owns the business meaning and acceptable use.

Data steward

The day-to-day caretaker who ensures definitions, quality rules, and metadata are maintained.

Data custodian

Usually part of IT, responsible for operating the systems that store data, including backups and security.

Data lifecycle management

Controlling data through stages such as creation/collection, storage, use/processing, sharing, archiving/retention, and disposal/destruction.

Data classification

Labels data based on sensitivity and criticality, affecting access controls, encryption expectations, retention rules, and monitoring priorities.

OLTP (Online Transaction Processing)

Supports day-to-day transactions with fast inserts/updates and many concurrent users.

OLAP (Online Analytical Processing)

Supports analytics with complex reads and aggregations across time.

ETL (Extract, Transform, Load)

A process where data is extracted, transformed in a staging area, and then loaded into a target repository.

ELT (Extract, Load, Transform)

Data is loaded into the target system first, then transformed within that environment.

Primary key (PK)

A unique identifier for a row in a database table.

Foreign key (FK)

A field in one table that references the primary key in another table, establishing a relationship.

Normalization

The process of organizing tables to reduce redundancy and avoid anomalies in databases.

Data quality

Fitness for use of data, including dimensions like accuracy, completeness, consistency, timeliness, validity, and uniqueness.

Metadata

Data that describes other data, helping users understand and use data appropriately.

Data lineage

The process of tracking data from origin through transformations to final outputs, ensuring traceability.

RPO (Recovery Point Objective)

The maximum acceptable amount of data loss, defined in time.

RTO (Recovery Time Objective)

The maximum acceptable time to restore systems after a failure.

Master data

Core reference data used across processes, including customers, vendors, products, and accounts.

Data warehouse

A centralized repository designed for reporting and analytics, integrating data from multiple sources.

Data lake

A storage repository that holds a vast amount of raw data in its native format until needed.

Access controls

Security measures that restrict access to certain data based on user roles.

Inner join

A SQL operation that returns rows with matching keys in both joined tables.

Left join

A SQL operation that returns all rows from the left table and matched rows from the right table, filling with nulls where no match exists.

Least privilege

An access control principle ensuring that users receive only the access necessary to perform their job duties.

Data extraction

The process of pulling data from source systems for use in reporting or analysis.

Data cleansing

The process of fixing or removing incorrect, corrupted, or improperly formatted data.