Summary
In this chapter, you learned about outliers, their definition, common causes, and how to deal with them. You were also introduced to methods for identifying outliers using Python and R, taking into account the number of variables and their types.
Another focus of this chapter was on filling in missing values in tabular and time series datasets. You also learned how to diagnose missing values and implement imputation techniques using R. Next, you applied these imputation algorithms in Power BI.
In the next chapter, we will explore how you can use machine learning algorithms in Power BI without Premium or Embedded capabilities.
