Data modeling, contrary to be nearing obsolescence, remains crucial for data analysts aiming to enhance their reporting speed and deepen their insights into business operations. Bernard Obeng Boateng’s Data Modeling with Microsoft Excel has emerged as a fantastic resource for this topic.
Despite Power Pivot’s presence in Excel for over a decade, its capability to build relational models is not widely recognized. Boateng’s book addresses this gap, offering a comprehensive guide on utilizing this underexplored feature. His empathetic approach is particularly noteworthy; he acknowledges the typical challenges faced by analysts, such as slow reports and cumbersome dashboards, guiding the reader without presuming their level of expertise. This reader-centric style makes the book an accessible and engaging read.
From Basics to Advanced Techniques
Boateng delves into the ‘why’ before the ‘how’, helping readers understand the advantages of using a relational data model over flat tables with practical, real-world examples. He skillfully demystifies the process of arranging and normalizing data, addressing the often-overlooked related area of data preparation with Power Query.
An intriguing part of the book focuses on cube functions, a lesser-known yet valuable aspect of Excel data modeling. This inclusion is particularly beneficial for readers unfamiliar with the transformation of data model logic into practical worksheet formulas.
Beyond Data Modeling: Visualization and Dashboards
Boateng doesn’t stop at the back end; he extends his discussion to front end applications, such as data visualization and dashboards. This section links the importance of data modeling to its ultimate purpose: creating meaningful, user-focused end products. It demonstrates that data modeling is not just about the technical process but also about translating data into impactful visual narratives.
Data Modeling with Microsoft Excel stands out as an essential guide for anyone seeking to master data modeling in Excel. It covers the entire process, from initial data markup to the creation of final dashboards, providing a well-scoped, practical approach for professional implementation.
In conclusion, Boateng’s book is a significant contribution to the field, offering a perfect balance of depth and accessibility. It’s a must-read for those looking to harness the full potential of Excel for data modeling.
Have you delved into Boateng’s book? What are your impressions, and what other resources have you found helpful in relational data modeling with Excel? Share your experiences and recommendations in the comments below.
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