The book emphasizes four important topics:

Chapter 1: Overview: Building Data Analytic Systems with Hadoop.- Chapter 2: A Scala and Python Refresher.- Chapter 3: Standard Toolkits for Hadoop and Analytics.- Chapter 4: Relational, noSQL, and Graph Databases.- Chapter 5: Data Pipelines and How to Construct Them.- Chapter 6: Advanced Search Techniques with Hadoop, Lucene, and Solr.- Chapter 7: An Overview of Analytical Techniques and Algorithms.- Chapter 8: Rule Engines, System Control, and System Orchestration.- Chapter 9: Putting it All Together: Designing a Complete Analytical System.- Chapter 10: Data Visualizers: Seeing and Interacting with the Analysis.- Chapter 11: A Case Study in Bioinformatics: Analyzing Microscope Slide Data.- Chapter 12: A Bayesian Analysis Software Component: Identifying Credit Card Fraud.- Chapter 13: Searching for Oil: Geological Data Analysis with Mahout.- Chapter 14: 'Image as Big Data' Systems: Some Case Studies.- Chapter 15:A Generic Data Pipeline Analytical System.- Chapter 16: Conclusions and The Future of Big Data Analysis.