Summary
This chapter covered the data analytics layer, which is a vital element in a data lakehouse. We explained that transforming data into insights is the core aim of any data analytics platform, and we looked at how this can be achieved in detail.
We started by exploring some of the different business requirements of data analytics. Then, we covered different users and how they interact with data analytics. We showed how descriptive and advanced analytics form the broad categories of analytics that organizations typically require. We then discussed the characteristics of these categories in detail. Next, we drilled down into different analytics capabilities within these categories. After that, we discussed five analytics capabilities that are important for fulfilling the analytical needs of an organization.
We then mapped the three components of the data analytics layer with their analytics capabilities. Finally, the chapter discussed the sub-components required in each of...
