Exploring Data Analytics Concepts
Now that we understand how to store our transactional data in databases, in this chapter, we will address generating intelligence with that data through data analytics. In modern software architecture, analytical workloads are important for processing data in near-real-time and creating smarter solutions based on that data.
These concepts are important for understanding the logic behind Azure Data Analytics services, which are evaluated in the DP-900 test and can be used in your projects.
By the end of this chapter, you will understand data ingestion, processing, modeling, and visualization concepts, which make up the end-to-end data flow for data analytics.
In this chapter, we will cover the following topics:
- Data ingestion and processing
- Analytical data store
- Analytical data model
- Data visualization
