There are 4 primary styles or approaches for data preparation. Which one is right for your organization? It’s an important decision for data analysts and data practitioners, who often spend the majority of their time (up to 80%) during data science projects painstakingly preparing data for analysis.
Download this eBook to learn:
- Paradigms and comparison formats to consider when evaluating the 4 data prep styles
- Strengths, challenges, and use cases inherent with each data prep style
- Strategies for deciding which data prep style best fits your needs