Summary

Big Data analytics with Hadoop and Spark is broadly classified into two major categories: data analytics and data science. While data analytics focuses on past and present statistics, data science focuses on future statistics. While data science projects are iterative in nature, data analytics projects are not iterative.

Apache Hadoop provides you with distributed storage and resource management and Spark provides you with in-memory performance for Big Data analytics. A variety of tools and techniques are used in Big Data analytics depending on the type of use cases and their feasibility.

The next chapter will help you get started with Hadoop and Spark.