This book provides a practitioner’s approach to some of the key techniques and tools used in Big Data analytics. In many cases, Big Data analytics integrate structured and unstructured data with real-time feeds and queries, opening new paths to innovation and insight. For scientific efforts, Big Data analytics enable new avenues of investigation with potentially richer results and deeper insights than previously available. For businesses, Big Data helps drive efficiency, quality, and personalized products and services, producing improved levels of customer satisfaction and profit. Introduction Big Data is creating significant new opportunities for organizations to derive new value and create competitive advantage from their most valuable asset: information. Chapter 9: Advanced Analytical Theory and Methods: Text Analysis 1.
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Chapter 8: Advanced Analytical Theory and Methods: Time Series Analysis 1. Chapter 7: Advanced Analytical Theory and Methods: Classification 1. Chapter 6: Advanced Analytical Theory and Methods: Regression 1. 5.5 An Example: Transactions in a Grocery Store 6. Chapter 5: Advanced Analytical Theory and Methods: Association Rulesġ. Chapter 4: Advanced Analytical Theory and Methods: Clustering 1. 3.3 Statistical Methods for Evaluation 4. Chapter 3: Review of Basic Data Analytic Methods Using R 1. 2.8 Case Study: Global Innovation Network and Analysis (GINA) 9. 1.3 Key Roles for the New Big Data Ecosystem 4. 1.2 State of the Practice in Analytics 3. Chapter 1: Introduction to Big Data Analytics 1.