Data Transformation and Structuring

О курсе

Build a strong foundation in preparing, transforming, and structuring data for analysis with this comprehensive Data Transformation and Structuring course. You’ll learn how to filter, subset, and reshape datasets; apply joins and merges; create derived columns; and use subqueries or CTEs to organize multi-step data retrieval. Expanding beyond transformation alone, you’ll interpret linear regression outputs, explore correlation techniques, and understand the core components of hypothesis testing—giving you both practical and analytical insight into data behavior. Through hands-on practice across Python, SQL, and Power BI, you’ll work with real-world tools to clean, reshape, and model datasets effectively. This multi-author course combines the expertise of Fractal Analytics, SAS, Microsoft, IBM, and Cloudera, offering diverse perspectives on how different platforms approach data wrangling and analytical preparation. You’ll progress from essential filtering and transformation workflows to more advanced skills like pivoting/unpivoting, statistical exploration, and regression-based interpretation. Ideal for aspiring data analysts, BI professionals, and learners seeking practical, tool-agnostic transformation skills, this course equips you to confidently manipulate and structure data for meaningful insights and analysis.

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