DP-900 - Describe Core Data Concepts (30% of the exam) - Section 1.3

Describe common data workloads including transactional and analytical processing.

Compare OLTP workloads (high-frequency, short transactions) with OLAP workloads (complex aggregations over large datasets), and distinguish batch processing from stream processing. Recognise where ETL and ELT pipelines fit and when each pattern applies.

OLTPOLAPbatch processingstream processingETL and ELT

Practice question for this objective

Free sampleDescribe Core Data Conceptseasy

Analytical data processing typically uses read-only or read-mostly systems that store vast volumes of historical data or business metrics. Is this statement correct?

AYes Correct
BNo

Analytical processing is read-mostly over large volumes of historical data and snapshots. Analytical data processing relies on read-only or read-mostly systems that hold large volumes of historical data or business metrics, with analytics based on snapshots taken at a point in time.

Why A is correct: Correct. Analytical data processing relies on read-only or read-mostly systems that hold large volumes of historical data or business metrics, with analytics based on snapshots taken at a point in time.

Why B is wrong: Answering No would wrongly attribute high-volume read and write transactions to analytics; that pattern belongs to transactional OLTP systems, not analytical processing.

See more DP-900 practice questions, answers explained.

Exam traps in Describe Core Data Concepts

Answers that look right on this material and are not. Each one is a distractor from a different question in the DP-900 bank for this domain.

ELT keeps the analytical data read-only, while ETL allows the source records to be updated in place
Why it is wrong: Tempting because analytical stores are read-mostly, but the read-only nature is not what separates the two patterns; the ordering of transformation does.
Data is transformed before it is ever loaded into storage
Why it is wrong: Transforming before loading describes ETL, where data is extracted, transformed, and only then loaded - not the ELT ordering.
Database administrator, who tunes databases
Why it is wrong: The DBA focuses on availability, performance, security, and backups, not building cleansing and transformation activities.

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