Data inventory and data mapping both are essential components of data management and compliance with privacy regulations. Here’s a brief introduction to both of them.

Data inventory can be considered as a comprehensive catalog of all organizational datasets that can identify and record various types of data collected, stored, processed, and shared. Data inventory can include other important information such as the source of data, data format, its storage locations, and the data’s lifecycle.

According to Experian, 60% of businesses lack a complete understanding of their data which leads to wasted resources and also affects data-driven decision-making. Having a well-maintained and thorough data inventory can help organizations understand their data landscape and help them with better data governance, risk management, and decision-making.

Data mapping, on the other hand, refers to the process of creating a well-detailed blueprint of how data flows within an organization. It is used to track the data movement from one system to another and identifies how data is collected, stored, and shared. So, it is simply a process of mapping data fields between source and destination systems. It ensures the integrity of data is maintained, and also data is consistent throughout its journey.

It is particularly beneficial for data integration, migration, and transformation projects to maintain the quality of data.
But data inventory and data mapping aren’t confined just to this. They have high importance in the world of data science. Check out our detailed guide on data inventory and data mapping to understand more about them, their benefits, and processes which will help you excel in your data science career.