This eBook provides a structured framework for building a reliable and scalable data preparation strategy. It walks through five core steps: data blending, exploration, cleansing, profiling, and ETL. The guide explains why poor data preparation leads to inaccurate insights, wasted time, and costly errors, and shows how automation improves speed, repeatability, and trust. It emphasizes moving away from manual spreadsheets toward visual, automated workflows that support governance and collaboration. The eBook positions data preparation as the foundation of analytics, AI, and enterprise decision-making.

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