IBM InfoSphere Information Governance Catalog

Data mapping identifies the data source or source system (i.e., terminology, data set, database, etc.) the data is coming from, or being mapped from, and the target repository (i.e., database, data warehouse, data lake, cloud-based system, or application, etc.) it’s going to be or being mapped to.

Data governance, at its core, is establishing trust in data – the quality and sources of data, the integrity and the use of data, and the security of data during the lifecycle of data within the enterprise. Data lineage plays an important role in your data governance framework and overall data management strategy by providing visibility into how data flows throughout your environment as well as transparency in the sourcing, structure, and evolution of your data.  

When you have a complete overview of all your data flows, sources, transformations, and dependencies, you have control of your data assets. You can speak to the accuracy and quality of your data and have confidence in your data information and reports. By giving you a full overview of how your data moves across systems, where it originated, how it transforms along the way, and how it’s interconnected, data lineage can help you to ensure the quality of your data, reinforce your overall data management strategy, and increase trust in your data.

An invaluable tool for analyzing data dependency is the lineage graph generated by MANTA. You are able to see exactly how each attribute is related to another, how a particular transformation impacts them, or how a particular transformation has affected the data. Knowing the answers to such questions will give you more power and control over dependencies and will enable you to deploy more automated techniques.