DA0-002 cheat sheet

Exam at a glance

Domain weightings

How much of the exam each domain covers. Spend your study time in proportion — the heavier the domain, the more questions you'll see.

Key terms

ETL

ETL (Extract, Transform, Load) is a data-integration pattern that extracts data from sources, transforms it, then loads it into a target store. Data+ covers ETL versus ELT as core integration concepts.

ELT

ELT (Extract, Load, Transform) loads raw data into the target system first and transforms it there, often used with cloud data warehouses and lakes. Data+ contrasts it with ETL.

Data warehouse

A data warehouse is a central repository optimized for analytical querying (OLAP) of integrated, structured data. Data+ covers it alongside data lakes and OLTP versus OLAP.

Data lake

A data lake is a storage repository that holds large volumes of raw data in native formats — structured, semi-structured, and unstructured — until needed. Data+ covers it within data environments.

OLAP

OLAP (Online Analytical Processing) is a class of systems optimized for complex analytical queries and aggregations over large datasets. Data+ contrasts OLAP with transactional OLTP systems.

OLTP

OLTP (Online Transaction Processing) is a class of systems optimized for high volumes of short, transactional read/write operations. Data+ contrasts OLTP with analytical OLAP systems.

Data cleaning

Data cleaning is the process of detecting and correcting errors — missing values, duplicates, outliers, and inconsistencies — to improve data quality. Data+ covers cleaning within data preparation.

Data profiling

Data profiling is the examination of data to summarize its structure, content, and quality before analysis. Data+ covers profiling as part of acquiring and preparing data.

Outlier

An outlier is a data point that differs significantly from other observations and may indicate error or genuine variation. Data+ covers identifying and handling outliers during preparation and analysis.

Descriptive statistics

Descriptive statistics summarize a dataset using measures of central tendency (mean, median, mode) and dispersion (range, variance, standard deviation). Data+ covers them as foundational analysis techniques.

Regression

Regression is a statistical method that models the relationship between a dependent variable and one or more independent variables. Data+ covers regression among its statistical analysis methods.

Correlation

Correlation measures the strength and direction of the linear relationship between two variables, without implying causation. Data+ covers correlation within analysis and interpretation.

Hypothesis testing

Hypothesis testing is a statistical procedure that uses sample data to evaluate a claim about a population, assessing significance with a p-value. Data+ covers it among statistical methods.

Data governance

Data governance is the framework of policies, ownership, stewardship, and standards that ensures data is accurate, secure, and used appropriately. Data+ dedicates a domain to governance, privacy, and lifecycle.

PII

PII (Personally Identifiable Information) is data that can identify an individual and is subject to privacy regulations and protection controls. Data+ covers PII within data governance and privacy.