Data Analytics with Hadoop: An Introduction for Data Scientists

Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce.

Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data.

• Understand core concepts behind Hadoop and cluster computing
• Use design patterns and parallel analytical algorithms to create distributed data analysis jobs
• Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase
• Use Sqoop and Apache Flume to ingest data from relational databases
• Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames
• Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib

• Hadoop: The Definitive Guide: Storage and Analysis at Internet Scale
• Graph Databases: New Opportunities for Connected Data
• Programming Hive
• Learning Spark: Lightning-Fast Big Data Analysis
• SQL Queries for Mere Mortals: A Hands-On Guide to Data Manipulation in SQL (3rd Edition)
• HBR Guide to Persuasive Presentations (HBR Guide Series) (Harvard Business Review Guides)
• Big Data: A Revolution That Will Transform How We Live, Work, and Think
• Practical Statistics for Data Scientists: 50 Essential Concepts
• Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results
• Spark: The Definitive Guide: Big Data Processing Made Simple