Today's applications generate massive volumes of data from users. This creates unique challenges for storing and querying the information. The systems need to be able to support high volumes of read and write operations without compromising the performance of the application. Developers often struggle to figure out the right tools -- SQL and NoSQL -- for implementation.
The modern data warehouse pattern makes it easier than ever to deal with the increasing volume of data. This pattern enables massive, global-scale writes operations while making the information instantly available for reporting and insights.
In this session, we'll explore the pattern in depth, the various services on Azure that support this pattern, and how to choose the right ones for your needs. We'll explore how to achieve highly concurrent, scalable systems with these tools, as well as the common mistakes developers make implementing the MDW pattern. Learn the secrets to combining Data Lakes, Delta, Databricks, Azure SQL Hyperscale, Synapse Analytics, and more!
You will learn:
- Define and understand how to implement the MDW architecture pattern
- How to determine appropriate Azure SQL and NoSQL solutions for a workload
- Understand how to ingest and report against high volume data