Data Scrubbing Role in Data Warehousing

Data scrubbing is a crucial process in data management, particularly before data is loaded into a data warehouse.

Statement (A) Analysis

Statement (A) claims that data scrubbing upgrades the quality of data before it moves into a data warehouse. This is accurate. Data scrubbing involves identifying and correcting errors, inconsistencies, and inaccuracies in data. Its primary goal is to ensure the data is clean, complete, and reliable, thereby improving its overall quality. This preparation step is essential for effective data warehousing.

• Data Scrubbing Purpose: Enhance data accuracy and consistency.
• Timing: Performed before data loading into the data warehouse.
• Result: Improved data quality.

Therefore, Statement (A) is true.

Statement (B) Analysis

Statement (B) defines data scrubbing as rejecting data from a data warehouse to create indexes. This is incorrect.

• Data scrubbing focuses on data improvement, not rejection from the warehouse.
• Rejecting data is typically part of data loading or governance rules, not the definition of scrubbing itself.
• Creating indexes is a separate database optimization task, unrelated to the core function of data scrubbing.

Therefore, Statement (B) is false.

Conclusion on Statements

Based on the analysis, Statement (A) is true, and Statement (B) is false. This corresponds to the option where (A) is true and (B) is false.