Relational databases such as the Azure SQL database are designed for transactional workloads and optimized for Online transactional processing (OLTP) workloads, while data warehouse or Online Analytical Processing (OLAP) systems are optimized for reporting and analytics. Data in the data warehouse is cleaned, enriched, and transformed so that it can act as a single source of truth that users can trust. A modern data warehouse architecture suggests bringing all your structured and unstructured data into a Data Lake and cleansing, enriching, and transforming data before loading it into your data warehouse.

The Dynamics 365 product team is working toward enabling this modern data warehouse concept for Finance and Operations application by integrating Finance and Operations data in Azure Data Lake. But before we start discovering Finance and Operations integration with Data Lake, let's learn about some basic technologies in Azure data that are used to support end-to-end scenarios.