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Index
Cover
Title Page
Copyright
Table of Contents
Introduction
About This Book
Foolish Assumptions
Icons Used in This Book
Beyond the Book
Where to Go from Here
Part 1: Getting Started with Data Science
Chapter 1: Wrapping Your Head Around Data Science
Seeing Who Can Make Use of Data Science
Inspecting the Pieces of the Data Science Puzzle
Exploring Career Alternatives That Involve Data Science
Chapter 2: Tapping into Critical Aspects of Data Engineering
Defining Big Data and the Three Vs
Identifying Important Data Sources
Grasping the Differences among Data Approaches
Storing and Processing Data for Data Science
Part 2: Using Data Science to Extract Meaning from Your Data
Chapter 3: Machine Learning Means … Using a Machine to Learn from Data
Defining Machine Learning and Its Processes
Considering Learning Styles
Seeing What You Can Do
Chapter 4: Math, Probability, and Statistical Modeling
Exploring Probability and Inferential Statistics
Quantifying Correlation
Reducing Data Dimensionality with Linear Algebra
Modeling Decisions with Multiple Criteria Decision-Making
Introducing Regression Methods
Detecting Outliers
Introducing Time Series Analysis
Chapter 5: Grouping Your Way into Accurate Predictions
Starting with Clustering Basics
Identifying Clusters in Your Data
Categorizing Data with Decision Tree and Random Forest Algorithms
Drawing a Line between Clustering and Classification
Making Sense of Data with Nearest Neighbor Analysis
Classifying Data with Average Nearest Neighbor Algorithms
Classifying with K-Nearest Neighbor Algorithms
Solving Real-World Problems with Nearest Neighbor Algorithms
Chapter 6: Coding Up Data Insights and Decision Engines
Seeing Where Python and R Fit into Your Data Science Strategy
Using Python for Data Science
Using Open Source R for Data Science
Chapter 7: Generating Insights with Software Applications
Choosing the Best Tools for Your Data Science Strategy
Getting a Handle on SQL and Relational Databases
Investing Some Effort into Database Design
Narrowing the Focus with SQL Functions
Making Life Easier with Excel
Chapter 8: Telling Powerful Stories with Data
Data Visualizations: The Big Three
Designing to Meet the Needs of Your Target Audience
Picking the Most Appropriate Design Style
Selecting the Appropriate Data Graphic Type
Testing Data Graphics
Adding Context
Part 3: Taking Stock of Your Data Science Capabilities
Chapter 9: Developing Your Business Acumen
Bridging the Business Gap
Traversing the Business Landscape
Surveying Use Cases and Case Studies
Chapter 10: Improving Operations
Establishing Essential Context for Operational Improvements Use Cases
Exploring Ways That Data Science Is Used to Improve Operations
Chapter 11: Making Marketing Improvements
Exploring Popular Use Cases for Data Science in Marketing
Turning Web Analytics into Dollars and Sense
Building Data Products That Increase Sales-and-Marketing ROI
Increasing Profit Margins with Marketing Mix Modeling
Chapter 12: Enabling Improved Decision-Making
Improving Decision-Making
Barking Up the Business Intelligence Tree
Using Data Analytics to Support Decision-Making
Increasing Profit Margins with Data Science
Chapter 13: Decreasing Lending Risk and Fighting Financial Crimes
Decreasing Lending Risk with Clustering and Classification
Preventing Fraud Via Natural Language Processing (NLP)
Chapter 14: Monetizing Data and Data Science Expertise
Setting the Tone for Data Monetization
Monetizing Data Science Skills as a Service
Selling Data Products
Direct Monetization of Data Resources
Pricing Out Data Privacy
Part 4: Assessing Your Data Science Options
Chapter 15: Gathering Important Information about Your Company
Unifying Your Data Science Team Under a Single Business Vision
Framing Data Science around the Company’s Vision, Mission, and Values
Taking Stock of Data Technologies
Inventorying Your Company’s Data Resources
People-Mapping
Avoiding Classic Data Science Project Pitfalls
Tuning In to Your Company’s Data Ethos
Making Information-Gathering Efficient
Chapter 16: Narrowing In on the Optimal Data Science Use Case
Reviewing the Documentation
Selecting Your Quick-Win Data Science Use Cases
Picking between Plug-and-Play Assessments
Chapter 17: Planning for Future Data Science Project Success
Preparing an Implementation Plan
Supporting Your Data Science Project Plan
Executing On Your Data Science Project Plan
Chapter 18: Blazing a Path to Data Science Career Success
Navigating the Data Science Career Matrix
Landing Your Data Scientist Dream Job
Leading with Data Science
Starting Up in Data Science
Part 5: The Part of Tens
Chapter 19: Ten Phenomenal Resources for Open Data
Digging Through data.gov
Checking Out Canada Open Data
Diving into data.gov.uk
Checking Out US Census Bureau Data
Accessing NASA Data
Wrangling World Bank Data
Getting to Know Knoema Data
Queuing Up with Quandl Data
Exploring Exversion Data
Mapping OpenStreetMap Spatial Data
Chapter 20: Ten Free or Low-Cost Data Science Tools and Applications
Scraping, Collecting, and Handling Data Tools
Data-Exploration Tools
Designing Data Visualizations
Communicating with Infographics
Index
About the Author
Advertisement Page
Connect with Dummies
End User License Agreement
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