Practical Data Preparation: Solutions to the Top 5 Most Common MistakesData preparation has always been one of the most time consuming tasks of the data science lifecycle.
Over the years, this tedious process has become more efficient thanks to tools that speed up the practice, notably through automation. However, the data preparation phase of the data science lifecycle remains a significantly time-consuming step that needs to be optimized in order to scale AI across the organization and complete more projects faster.
Report Snap Shot
In this ebook, we will go over five common mistakes that arise during data preparation to help analysts upskill, paving the road to becoming successful citizen data scientists.