Multiple choice technology platforms and products

The data in Data Warehouse is generally

  1. Clean Data

  2. Dirty Data

  3. Clean and Dirty Data

  4. None of above
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A Correct answer
Explanation

Data warehouses integrate data from multiple sources and apply ETL processes to clean, standardize, and deduplicate data. Clean data is essential for reliable analytics and reporting.

AI explanation

Data warehouses are fed through ETL (Extract, Transform, Load) pipelines specifically designed to cleanse, standardize, deduplicate, and validate data before it's loaded, because the warehouse exists to support reliable reporting and analytics. As a result, the data inside a warehouse is generally clean — inconsistencies, duplicates, and errors from source operational systems are expected to be resolved during the ETL/transformation stage. "Dirty data" or "clean and dirty data" would defeat the purpose of a warehouse, which is precisely to present a trustworthy, consistent view of historical data for decision-making; some noise can slip through in practice, but by design and intent the warehouse's data is treated as clean.

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