© 2018

Next-Generation Big Data

A Practical Guide to Apache Kudu, Impala, and Spark


Table of contents

  1. Front Matter
    Pages i-xxiii
  2. Butch Quinto
    Pages 1-5
  3. Butch Quinto
    Pages 7-56
  4. Butch Quinto
    Pages 57-99
  5. Butch Quinto
    Pages 113-158
  6. Butch Quinto
    Pages 375-406
  7. Butch Quinto
    Pages 407-476
  8. Butch Quinto
    Pages 477-493
  9. Butch Quinto
    Pages 495-506
  10. Butch Quinto
    Pages 507-536
  11. Butch Quinto
    Pages 537-548
  12. Back Matter
    Pages 549-557

About this book


Utilize this practical and easy-to-follow guide to modernize traditional enterprise data warehouse and business intelligence environments with next-generation big data technologies.

Next-Generation Big Data takes a holistic approach, covering the most important aspects of modern enterprise big data. The book covers not only the main technology stack but also the next-generation tools and applications used for big data warehousing, data warehouse optimization, real-time and batch data ingestion and processing, real-time data visualization, big data governance, data wrangling, big data cloud deployments, and distributed in-memory big data computing. Finally, the book has an extensive and detailed coverage of big data case studies from Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard.

What You’ll Learn:

  • Install Apache Kudu, Impala, and Spark to modernize enterprise data warehouse and business intelligence environments, complete with real-world, easy-to-follow examples, and practical advice
  • Integrate HBase, Solr, Oracle, SQL Server, MySQL, Flume, Kafka, HDFS, and Amazon S3 with Apache Kudu, Impala, and Spark
  • Use StreamSets, Talend, Pentaho, and CDAP for real-time and batch data ingestion and processing
  • Utilize Trifacta, Alteryx, and Datameer for data wrangling and interactive data processing
  • Turbocharge Spark with Alluxio, a distributed in-memory storage platform
  • Deploy big data in the cloud using Cloudera Director
  • Perform real-time data visualization and time series analysis using Zoomdata, Apache Kudu, Impala, and Spark
  • Understand enterprise big data topics such as big data governance, metadata management, data lineage, impact analysis, and policy enforcement, and how to use Cloudera Navigator to perform common data governance tasks
  • Implement big data use cases such as big data warehousing, data warehouse optimization, Internet of Things, real-time data ingestion and analytics, complex event processing, and scalable predictive modeling
  • Study real-world big data case studies from innovative companies, including Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard


Apache Kudu Kudu Apache Spark Spark Apache Impala Impala Big Data Hadoop Apache Cloud Cloud computing Internet of Things (IOT) Real-time visualization Big data architecture Enterprise big data Distributed in-memory computing

Authors and affiliations

  1. 1.PlumptonAustralia

About the authors

Butch Quinto is Director of Analytics and Information Management at Deloitte where he leads technology innovation, strategy, solutions development and delivery, business development, vendor alliance, and due diligence. He is also Technical Leader of Deloitte’s ClearLight Lab, an R&D division that conducts innovative and game-changing research around advanced analytics, artificial intelligence, Internet of things, and big data.

Butch has more than 20 years of experience in various technical and leadership roles in several industries including banking and finance, telecommunications, government, utilities, transportation, e-commerce, retail, technology, manufacturing, and bioinformatics. Butch is a recognized thought leader and a frequent speaker at conferences and events. He is a contributor to the Apache Spark and Apache Kudu open source projects, founder of the Cloudera Melbourne User Group, and Deloitte’s Director of Alliance for Cloudera.

Bibliographic information

Industry Sectors
IT & Software
Consumer Packaged Goods
Finance, Business & Banking


“The book assumes familiarity with basic data analytics methods and tools, especially Hadoop, and presents high-level introductions to emerging technologies. It thus serves as a helpful guide for data analytics professionals seeking to keep pace with this dynamic and quickly advancing field.” (Harry J. Foxwell, Computing Reviews, April 10, 2019)