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Microsoft Excel 2010 Data Analysis and Business Modeling Data Analysis and Business Modeling

This book teaches business analysts how to use Microsoft Excel 2010 for sophisticated data analysis and business modeling through a series of practical, real-world examples and step-by-step tutorials.

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What it’s about

This is a practical, hands-on guide for any business professional who wants to move beyond basic spreadsheets and master Microsoft Excel 2010 for powerful data analysis and business modeling. Written by an award-winning professor and corporate trainer, the book translates a successful classroom experience to the page, using a learn-by-example approach to teach essential Excel functions (like VLOOKUP, INDEX, and text manipulation), financial modeling (NPV, IRR), optimization (Solver), simulation (Monte Carlo), and data summarization techniques (PivotTables, histograms). It covers key new features in Excel 2010 like Sparklines, Slicers, and PowerPivot. By working through hundreds of real-world problems—from scheduling workforces to pricing products and predicting elections—you will save hours of time, vastly improve your analytical capabilities, and learn to solve complex business problems more effectively.

The through-line

Who it’s for
A business analyst, manager, or MBA student who uses Excel daily but feels they are not using the software to its full potential. They want to be more efficient, solve more complex problems, and provide deeper, data-driven insights to their organization.
The problem
The reader struggles with time-consuming manual data manipulation, summarizing large datasets is cumbersome, and they lack the skills to build sophisticated models for forecasting, optimization, or risk analysis. The reader feels frustrated, inefficient, and stuck using only basic Excel features. They worry that their analytical skills are falling behind and that they are missing opportunities to add significant value.
The plan
  1. Master core Excel functions for data manipulation and lookup.
  2. Learn to build financial models for investment analysis (NPV, IRR).
  3. Use advanced tools like Data Tables, Goal Seek, and Solver for optimization and sensitivity analysis.
  4. Summarize and visualize data effectively using PivotTables, charts, and conditional formatting.
  5. Incorporate uncertainty into models using probability distributions and Monte Carlo simulation.
The payoff
The reader becomes a highly efficient and productive Excel power user, saving hours each week. · They can confidently build sophisticated models to analyze complex business problems, providing valuable, data-driven recommendations. · They gain a deeper understanding of business concepts like statistics, forecasting, and optimization, making them a more valuable asset to their organization and advancing their career.

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Additional reading

  • Data Analysis for Managers with Microsoft Excel · S. Christian Albright, Wayne L. Winston, and Christopher Zappe

    Referenced as a source for more advanced topics like creating custom web queries, suggesting it is a logical next step for readers.

  • Investment Science · David G. Luenberger

    Recommended for readers who want a more detailed and technical discussion of options pricing and real options theory.

  • Power Pricing · Robert J. Dolan and Hermann Simon

    Suggested for those wanting to gain deeper insights into product pricing strategies beyond the models presented in the book.

  • Predicting Presidential Elections and Other Things · Roy Fair

    This is the source for the presidential election forecasting model used as a major example of multiple regression in Chapter 54.

  • Mathletics · Wayne L. Winston

    Written by the book's author, it covers the application of mathematics in sports, aligning with the book's use of sports analytics examples (e.g., rating NFL teams).

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