Practical Data Preparation: Solutions to the Top 5 Most Common Mistakes

Data 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.

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