Understanding the end-to-end scenario

Real-time analytics allows for a variety of valid use cases including streaming data processing, low-latency queries on large datasets, and querying complex formats such as nested JSON. There are three important concepts to understand:

• Eventstreams: This no-code experience captures, transforms, and routes events to destinations such as KQL databases or Fabric lakehouses.
• KQL databases: Data is stored and organized in tables that are organized in databases. A workspace can have multiple databases.
• KQL queryset: A KQL query is a request to process and display data in a specific manner. A queryset is a collection of queries from a particular workspace. Each query in a queryset can execute against different workspaces.

This chapter will focus on building a simplified real-time analytics architecture, as shown in Figure 5.1, but real-world scenarios often contain a wide array of data sources and downstream consumers. Not all data...