
Data Smart
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Free ChapterCover
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Credits
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About the Author
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About the Technical Editors
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Acknowledgments
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Introduction
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Chapter 1: Everything You Ever Needed to Know about Spreadsheets but Were Too Afraid to Ask
- Chapter 1: Everything You Ever Needed to Know about Spreadsheets but Were Too Afraid to Ask
- Some Sample Data
- Moving Quickly with the Control Button
- Copying Formulas and Data Quickly
- Formatting Cells
- Paste Special Values
- Inserting Charts
- Locating the Find and Replace Menus
- Formulas for Locating and Pulling Values
- Using VLOOKUP to Merge Data
- Filtering and Sorting
- Using PivotTables
- Using Array Formulas
- Solving Stuff with Solver
- OpenSolver: I Wish We Didn't Need This, but We Do
- Wrapping Up
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Chapter 2: Cluster Analysis Part I: Using K-Means to Segment Your Customer Base
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Chapter 3: Naïve Bayes and the Incredible Lightness of Being an Idiot
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Chapter 4: Optimization Modeling: Because That “Fresh Squeezed” Orange Juice Ain't Gonna Blend Itself
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Chapter 5: Cluster Analysis Part II: Network Graphs and Community Detection
- Chapter 5: Cluster Analysis Part II: Network Graphs and Community Detection
- What Is a Network Graph?
- Visualizing a Simple Graph
- Brief Introduction to Gephi
- Building a Graph from the Wholesale Wine Data
- How Much Is an Edge Worth? Points and Penalties in Graph Modularity
- Let's Get Clustering!
- There and Back Again: A Gephi Tale
- Wrapping Up
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Chapter 6: The Granddaddy of Supervised Artificial Intelligence—Regression
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Chapter 7: Ensemble Models: A Whole Lot of Bad Pizza
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Chapter 8: Forecasting: Breathe Easy, You Can't Win
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Chapter 9: Outlier Detection: Just Because They're Odd Doesn't Mean They're Unimportant
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Chapter 10: Moving From Spreadsheets into R
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Conclusion
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End User License Agreement
About this book
Data Science gets thrown around in the press like it's magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.
But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.
Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet.
Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype.
But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, math and the magic, behind big data.
- Publication date:
- November 2013
- Publisher
- Packt
- Pages
- 432
- ISBN
- 9781118661468