Summary

This chapter covered the general nature of temporal data, some specific instances of such data items in real-world applications, and why Cassandra is the best fit as a NoSQL data store to persist temporal data. Temporal data quite often come in different use cases of many applications. Data modeling of temporal data is very important in a Cassandra perspective for optimal storage and fast access to the data. Some common design patterns to model temporal data have been covered in this chapter. By focusing on a few aspects such as the partition key, primary key, clustering column, and the number of records stored into a wide row in Cassandra, very effective and high performing temporal data models can be built.

The 3Vs of big data, namely volume, variety, and velocity, pose another big challenge: the analysis of the data stored in NoSQL data stores such as Cassandra. What are the analytics use cases? How can the distributed data be processed? What are the data transformations that...