Data Smart, 2nd Edition

Data Smart, 2nd Edition

by Jordan Goldmeier
Released November 2023
Publisher(s): Wiley
ISBN: 9781119931386

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Book description

Want to jump into data science but don't know where to start?

Let's be real, data science is presented as something mystical and unattainable without the most powerful software, hardware, and data expertise. Real data science isn't about technology. It's about how you approach the problem.

In this updated edition of Data Smart: Using Data Science to Transform Information into Insight, award-winning data scientist and bestselling author Jordan Goldmeier shows you how to implement data science problems using Excel while exposing how things work behind the scenes.

Data Smart is your field guide to building statistics, machine learning, and powerful artificial intelligence concepts right inside your spreadsheet.

Inside you'll find:

  • Four-color data visualizations that highlight and illustrate the concepts discussed in the book
  • Tutorials explaining complicated data science using just Microsoft Excel
  • How to take what you’ve learned and apply it to everyday problems at work and life
  • Advice for using formulas, Power Query, and some of Excel's latest features to solve tough data problems
  • Smart data science solutions for common business challenges
  • Explanations of what algorithms do, how they work, and what you can tweak to take your Excel skills to the next level

Data Smart is a must-read for students, analysts, and managers ready to become data science savvy and share their findings with the world.

Table of contents

  1. Cover
  2. Table of Contents
  3. Title Page
  4. Introduction
    1. What Am I Doing Here?
    2. What Is Data Science?
    3. Do Data Scientists Actually Use Excel?
    4. Conventions
    5. Let's Get Going
    6. Notes
  5. 1 Everything You Ever Needed to Know About Spreadsheets but Were Too Afraid to Ask
    1. Some Sample Data
    2. Accessing Quick Descriptive Statistics
    3. Excel Tables
    4. Lookup Formulas
    5. PivotTables
    6. Using Array Formulas
    7. Solving Stuff with Solver
    8. Notes
  6. 2 Set It and Forget It: An Introduction to Power Query
    1. What Is Power Query?
    2. Sample Data
    3. Starting Power Query
    4. Filtering Rows
    5. Removing Columns
    6. Find & Replace
    7. Close & Load to…Table
    8. Note
  7. 3 Naïve Bayes and the Incredible Lightness of Being an Idiot
    1. The World's Fastest Intro to Probability Theory
    2. Separating the Signal and the Noise
    3. Using the Bayes Rule to Create an AI Model
    4. Let's Get This Excel Party Started
    5. Notes
  8. 4 Cluster Analysis Part 1: Using K-Means to Segment Your Customer Base
    1. Dances at Summer Camp
    2. Getting Real: K-Means Clustering Subscribers in Email Marketing
    3. K-Medians Clustering and Asymmetric Distance Measurements
  9. 5 Cluster Analysis Part II: Network Graphs and Community Detection
    1. What Is a Network Graph?
    2. Visualizing a Simple Graph
    3. Building a Graph from the Wholesale Wine Data
    4. Introduction to Gephi
    5. How Much Is an Edge Worth? Points and Penalties in Graph Modularity
    6. Let's Get Clustering!
    7. There and Back Again: A Gephi Tale
  10. 6 Regression: The Granddaddy of Supervised Artificial Intelligence
    1. Predicting Pregnant Customers at RetailMart Using Linear Regression
    2. Predicting Pregnant Customers at RetailMart Using Logistic Regression
    3. Note
  11. 7 Ensemble Models: A Whole Lot of Bad Pizza
    1. Getting Started Using the Data from Chapter 6
    2. Bagging: Randomize, Train, Repeat
    3. Boosting: If You Get It Wrong, Just Boost and Try Again
    4. Note
  12. 8 Forecasting: Breathe Easy: You Can't Win
    1. The Sword Trade Is Hopping
    2. Getting Acquainted with Time-Series Data
    3. Starting Slow with Simple Exponential Smoothing
    4. You Might Have a Trend
    5. Holt's Trend-Corrected Exponential Smoothing
    6. Multiplicative Holt-Winters Exponential Smoothing
    7. Forecast Sheets in Excel
  13. 9 Optimization Modeling: Because That “Fresh-Squeezed” Orange Juice Ain't Gonna Blend Itself
    1. Wait…Is This Data Science?
    2. Starting with a Simple Trade-Off
    3. Fresh from the Grove to Your Glass…with a Pit Stop Through a Blending Model
    4. Modeling Risk
    5. Notes
  14. 10 Outlier Detection: Just Because They’re Odd Doesn’t Mean They’re Unimportant
    1. Outliers Are (Bad?) People, Too
    2. The Fascinating Case of Hadlum v. Hadlum
    3. Terrible at Nothing, Bad at Everything
    4. Note
  15. 11 Moving on From Spreadsheets
    1. Getting Up and Running with R
    2. Doing Some Actual Data Science
  16. 12 Conclusion
    1. Where Am I? What Just Happened?
    2. Before You Go-Go
    3. Get Creative and Keep in Touch!
  17. Index
  18. Copyright
  19. Dedication
  20. About the Author
  21. About the Technical Editors
  22. Acknowledgments
  23. End User License Agreement

Product information

  • Title: Data Smart, 2nd Edition
  • Author(s): Jordan Goldmeier
  • Release date: November 2023
  • Publisher(s): Wiley
  • ISBN: 9781119931386