Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data

Contents

Introduction

Chapter 1 • Introduction to Big Data Analytics

1.1 Big Data Overview

1.1.1 Data Structures

1.1.2 Analyst Perspective on Data Repositories

1.2 State of the Practice in Analytics

1.2.1 BI Versus Data Science

1.2.2 Current Analytical Architecture

1.2.3 Drivers of Big Data

1.2.4 Emerging Big Data Ecosystem and a New Approach to Analytics

1.3 Key Roles for the New Big Data Ecosystem

1.4 Examples of Big Data Analytics

Summary

Exercises

Bibliography

Chapter 2 • Data Analytics Lifecycle

2.1 Data Analytics Lifecycle Overview

2.1.1 Key Roles for a Successful Analytics Project

2.1.2 Background and Overview of Data Analytics Lifecycle

2.2 Phase 1: Discovery

2.2.1 Learning the Business Domain

2.2.2 Resources

2.2.3 Framing the Problem

2.2.4 Identifying Key Stakeholders

2.2.5 Interviewing the Analytics Sponsor

2.2.6 Developing Initial Hypotheses

2.2.7 Identifying Potential Data Sources

2.3 Phase 2: Data Preparation

2.3.1 Preparing the Analytic Sandbox

2.3.2 Performing ETLT

2.3.3 Learning About the Data

2.3.4 Data Conditioning

2.3.5 Survey and Visualize

2.3.6 Common Tools for the Data Preparation Phase

2.4 Phase 3: Model Planning

2.4.1 Data Exploration and Variable Selection

2.4.2 Model Selection

2.4.3 Common Tools for the Model Planning Phase

2.5 Phase 4: Model Building

2.5.1 Common Tools for the Model Building Phase

2.6 Phase 5: Communicate Results

2.7 Phase 6: Operationalize

2.8 Case Study: Global Innovation Network and Analysis (GINA)

2.8.1 Phase 1: Discovery

2.8.2 Phase ...