Data traceability is the ability to ensure that your data is completely traceable across the entire landscape. This allows you to easily follow your data all the way back to its original source. In order to make clear and accurate insights, you must be able to track every transformation, dead-end, or link between the data points. Data traceability is important when looking at source systems as well as reports. It essentially accounts for all data, from source to current target. Without data traceability, you can’t confirm that all data is fully correct, which may impact future decisions. Data traceability also ensures the validity of your information since you can see the data’s entire journey, from origin to where it exists now.
In order to enforce and confirm data traceability, companies can implement automated data lineage. This allows BI teams to trace their data and fully understand how it flows and see any stops or transformations it underwent. With this visual depiction, BI and analytics professionals can pinpoint any dependencies within the entire data landscape. This includes different databases and processes which interact with the data. In addition, automated data lineage helps teams to handle any necessary migrations, system upgrades or consolidations, regulatory compliance, and account for any changes or report errors.