As businesses continue to generate massive amounts of data, the need for efficient data management solutions becomes increasingly important. This is where a data lake house comes in - an hybrid solution that combines the best features of a datalake and a data warehouse.
We explored how to build a data lakehouse using Azure Data Explorer (ADX) where the data flows from Azure SQL DB using Change Data Capture (CDC) through Azure Data Factory and events flowing from events hub.
This article is Part 2 in the series, here we will deploy this solution using Bicep, a powerful infrastructure as code (IaC) tool from Microsoft. With this guide, you'll be able to create a data lakehouse that can handle large volumes of data and provide valuable insights for your business.
An Azure account and a logged in user with admin permissions
We have products and orders from our operational DB (Azure SQL) and events coming from a stream in events hub.
In this demo I chose to add synthetic events using one-click ingestion, but you can create events and publish them to Events hub and they will be ingested using streaming ingestion to the bronzeClicks table.