En la cubierta: "A hands-on guide for programmers and data scientists"

1 Introduction - Part I. Graphics: Looking at Data -- 2 A Single Variable: Shape and Distribution -- 3 Two Variables: Establishing Relationships -- 4 Time As a Variable: Time-Series Analysis -- 5 More Than Two Variables: Graphical Multivariate Analysis -- 6 Intermezzo: A Data Analysis Session - Part II -- 7 Guesstimation and the Back of the Envelope -- 8 Models from Scaling Arguments -- 9 Arguments from Probability Models -- 10 What You Really Need to Know About Classical Statistics -- 11 Intermezzo: Mythbusting-Bigfoot, Least Squares, and All That - Part III. Computation: Mining Data -- 12 Simulations -- 13 Finding Clusters -- 14 Seeing the Forest for the Trees: Finding Important Attributes -- 15 Intermezzo: When More Is Different - Part IV. Applications: Using Data -- 16 Reporting, Business Intelligence, and Dashboards -- 17 Financial Calculations and Modeling -- 18 Predictive Analytics -- 19 Epilogue: Facts Are Not Reality

" Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications." -- P. [4]

PIT

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