March 2021
Beginner to intermediate
336 pages
9h 38m
English
Having a strong understanding of most common types of data workload is crucial to the delivery of successful projects.
Every workload has its particular approach and established best practices. Moreover, you have to choose carefully which engine best fits your needs to avoid having to rebuild the project from scratch in the middle of development or to avoid incurring unplanned costs and budget revisions.
In this chapter, we first compare various kinds of data workload to understand key differences between them. Then, we introduce the core concepts behind data analytics and visualization.
Skills covered in this chapter:
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