Summary

This chapter covered several data analysis aspects; it mainly discussed the data transformations. Data transformation is one of the major activity in data processing. Out of the many data processing patterns, Map/Reduce pattern deserves a special mention because it is being used in many batch processing and analysis use cases dealing with big data. Spark has been chosen as the tool of choice to explain the data processing activities. How a Map/Reduce kind of data processing task can be performed using Cassandra and Spark has been discussed, which is very powerful to perform online data analysis. This chapter also covered some of the commonly seen data transformations that are used in the data processing applications.

Many Cassandra design patterns have been covered so far in this book and this chapter concludes the discussions on the design patterns. If the design patterns are not being used in any real-world applications, it has only theoretical value. To give a practical approach...