In today's data-driven world, where information is the lifeblood of decision making, the seamless management and evolution of data is paramount. Data version control, like its software counterpart, allows organisations to maintain a historical record of data changes and facilitates a collaborative approach to data management. It provides an indispensable framework for tracking and managing changes to data, ensuring data integrity, collaboration and, most importantly, the systematic evolution of data integration processes.

But is data version control also becoming a key concept in data-driven projects, similar to the version control systems used in software development?

In this Session, we explore the importance of data version control in the context of data management, highlighting its key role in navigating the complexities of data integration and evolution. We present various projects and solutions such as dolt, DVC or lakeFS and show how they can be used effectively in projects on the Microsoft Data Platform.