LEARNING PATH: Big Data Analytics and Processing with Spark

Leverage the power of Apache Spark to perform efficient data processing and analytics on your data in real-time

About Course

Every year a large amount of data is generated which needs to be stored and analyzed. Apache Spark allows you to process such big data. The real power and value proposition of Apache Spark is its speed and platform to execute data science tasks. Spark's unique use case is that it combines ETL, batch analytic, real-time stream analysis, machine learning, graph processing, and visualizations to allow data scientists to tackle the complexities that come with raw unstructured data sets. Spark embraces this approach and has the vision to make the transition from working on a single machine to working on a cluster, something that makes data science tasks a lot more agile. So, if you're interested to learn big data processing and execute data science tasks efficiently, then go for this Learning Path.

Packt’s Video Learning Path is a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.

The highlights of this Learning Path are:

  • Implement efficient big data processing with Apache Spark
  • Understand ETL and deploy a Hadoop project to the cloud
  • Process and analyze streams of data with ease and perform machine learning efficiently