Big Data Storage Overview
Companies that use modern systems generate large volumes of heterogeneous data. This data must be exploited for marketing reasons or to make internal improvements to a product. This heterogeneous data demonstrates that a single data store is generally not the best approach.
It is also recommended to store different types of data in different data stores so that each one is geared toward a specific workload or usage pattern. If we use a combination of different data storage technologies, we are using what is called polyglot persistence. It is important to understand what Azure offers as a service for storing data warehouses and how we can use and analyze all that data.
In this chapter, we will explore big data storage and define Azure Data Lake Storage scalability, security, and cost optimization work. You will learn how to create a more secure, high-performance framework for data analytics.
In this chapter, we’re going to cover the following...