Microsoft Azure Data FundamentalsDescribe core data conceptsEasy
A data engineering team is responsible for transforming raw data from various sources into a clean, structured format suitable for analytical reporting. This process involves extracting data from source systems, cleaning and normalizing it, and then loading it into a data warehouse. Which common data workload best describes this entire sequence of operations?
- AOnline Transaction Processing (OLTP)
- BOnline Analytical Processing (OLAP)
- CStream Processing
- DExtract, Transform, Load (ETL)
Show answer & explanationAnswer & explanation
Correct answer: D. Extract, Transform, Load (ETL)
The entire sequence of extracting data from sources, cleaning/normalizing it (transform), and then loading it into a data warehouse for reporting is precisely what the Extract, Transform, Load (ETL) workload entails. It's a fundamental process in data warehousing.
Why the other options are wrong
- A. OLTP is for handling day-to-day transactions, not data preparation for analytics.
- B. OLAP is for querying and analyzing data in a data warehouse, not the process of populating it.
- C. Stream processing handles real-time data, whereas ETL often involves batch operations.
Extract, Transform, Load (ETL)
ETL is a data integration process that involves extracting data from source systems, transforming it into a desired format, and loading it into a target data store, typically a data warehouse.
- Consists of three main stages: Extract, Transform, Load.
- Used for data warehousing and data integration.
- Prepares data for analytical reporting.
Memory trick: ETL is the 'E'asy 'T'rick for 'L'oading data.