Summary
In this chapter, you began your journey into the practical aspects of data cleaning within Power BI. You covered some of the most common data cleaning steps in Power BI, including removing duplicates, handling missing data, splitting columns, merging tables, dealing with date formats, replacing values, and creating calculated columns versus measures.
The chapter also highlighted the importance of replacing values in your data. Outliers, incorrect values, or inconsistent formats can hinder analysis. You learned about various scenarios where replacing values is necessary and used the Replace Values function in Power Query to fix errors and standardize data.
Lastly, the chapter explored the difference between calculated columns and measures in Power BI and explained when to use each option and their respective benefits. Calculated columns are best suited for row-level calculations, while measures are ideal for aggregations and calculations based on visual context. The chapter...
