A recent book by George Mount, titled "Modern Data Analytics in Excel: Using Power Query, Power Pivot, and Other Tools," presents a fresh perspective on utilizing Excel not merely as a spreadsheet but as a comprehensive analytical platform. Unlike traditional literature that focuses on basic functions and tricks, Mount emphasizes the architectural approach to data analytics, guiding readers through the entire analytical process from data storage to the selection of appropriate tools for specific tasks.
The book positions Excel as an entry point connecting self-service analytics to more complex systems, integrating tools like Power Query, Power Pivot, DAX, and dynamic arrays into a cohesive analytical pipeline. A significant theme throughout is the importance of data quality and structure, with the concept of "tidy data" serving as a foundation for effective analysis. This principle, which promotes a clean and organized data format, enhances the ease of working with formulas, pivot tables, and other analytical features within Excel.
Targeted at advanced users—including business analysts, financial analysts, and data analysts—the book assumes readers possess a basic proficiency in Excel but are seeking to tackle more sophisticated analytical challenges. It caters to professionals who often work with raw, dynamic data but may not transition to programming languages or business intelligence platforms.
One of the book's standout features is its conceptual coherence. Mount skillfully explains the rationale behind choosing certain tools over others in specific contexts, addressing the compromises involved. The book's structure logically progresses from the fundamentals of data organization to modern analytics tools, gradually expanding the reader's understanding of "modern Excel."
The initial chapters redefine Excel tables as foundational objects of analytics, stressing that proper headers, data types, and tidy structures are essential for effective automation. A substantial focus is placed on Power Query as an ETL tool, where the author discusses data transformation processes, emphasizing reproducibility and the principle of "one click—one update."
Further into the book, readers are introduced to dynamic arrays and the latest Excel formulas, showcasing their evolution into robust tools for filtering, sorting, and aggregating data. The concluding chapters explore the integration of Excel with augmented analytics, including AI features and machine learning capabilities, while candidly addressing Excel's limitations compared to more specialized tools.
Overall, "Modern Data Analytics in Excel" provides a valuable resource for those navigating the intersection of Excel and advanced analytics. It signifies a shift in how Excel can be perceived in the data science landscape, potentially impacting market dynamics and encouraging competitors to rethink their strategies as Excel continues to evolve as a powerful analytical tool.
Informational material. 18+.
