Data analytics, machine learning and statistical testing are all powerful tools for data science. These techniques all have one thing in common: the quality of the output is largely dependent on the quality of the data input!
This session will walk through three scenarios of transforming and manipulating messy data to prepare for analytics. The data from each scenario will be shaped and cleaned with both Power Query in Power BI and tidyverse packages in R Studio. The techniques demonstrated in these examples can be transferred to prepare messy data from numerous other business scenarios!
The slide deck and example files from the session can be downloaded here.