In this chapter, we covered details on understanding enterprise data, its features and categories. We then moved on to define Big Data with the core data definition from enterprise data. We also looked at the paradigm shift that Big Data has brought in and how the market is gearing up to use the technology advancements to handle the Big Data challenges. We also saw how traditional approaches no longer fit the Big Data context and new tools and techniques are being adopted. We also familiarized you with data analytics techniques, their purpose, and a typical data science life cycle.
In the next chapter, we will learn about Greenplum UAP. We will take a deep dive into the differentiating architectural patterns that make it suitable for advanced and Big Data analytics. In terms of hardware as well as software, we would be drilling into each of the modules and their relevance in the current context on analytics in discussion.