Big data analytics is revolutionizing the way businesses are run and has paved the way for several hitherto unimagined opportunities. Almost every enterprise, individual researcher, or investigative journalist has lots of data to process. We need a concise approach to start from raw data and arrive at meaningful insights based on the questions at hand.
We have covered various aspects of data science using Apache Spark in previous chapters. We started off discussing big data analytics requirements and how Apache spark fits in. Gradually, we looked into the Spark programming model, RDDs, and DataFrame abstractions and learnt how unified data access is enabled by Spark datasets along with the streaming aspect of continuous applications. Then we covered the entire breadth of the data analysis life cycle using Apache Spark followed by machine learning. We learnt structured and unstructured data analytics on Spark and explored the visualization aspects for...