Chapter 1 – Introduction to Power BI Data Cleaning

  1. B – 50-80%
  2. D – Power Query, data modeling, DAX formulas
  3. C – Data transformation and preparation
  4. C – As a formula language for creating calculations and measures
  5. B – To bridge the gap between relational databases and spreadsheet tools
  6. D – It can be used for both calculations and querying within Power BI
  7. B – It enhances clarity and reduces ambiguity

Chapter 2 – Understanding Data Quality and Why Data Cleaning is Important

  1. A – The extent to which data represents true values and attributes
  2. D – Human errors during data entry
  3. B – Data completeness
  4. B – It helps maintain data integrity and accuracy
  5. B – A culture of data stewardship
  6. A – Proactively identifying and addressing data quality ...

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