Chapter 9 – Advanced Data Cleaning Techniques

1. C – Fuzzy matching and fill down – They are the two essential techniques discussed in the chapter for cleaning and preparing data using the Query Editor in Power BI
2. C – Range from 0 to 1, indicating no to perfect similarity – In the context of fuzzy matching, the similarity score ranges from 0 to 1, indicating no to perfect similarity
3. D – When working with time series data and maintaining data continuity – The fill down technique in Power BI’s Query Editor is particularly useful in this scenario
4. D – Regularly validate the results of data cleaning efforts and maintain documentation – This is a crucial best practice emphasized when working with fuzzy matching and fill down in Power BI
5. C – To extend the capabilities of Power BI by leveraging external ecosystems – This is the primary purpose of using custom data scripts in languages such...