Data Cleaning with Power BI

Assessments

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 ...