We have built BI and analytics environments for almost 3 decades. Implementation teams have gotten very good at gathering data, integrating it, keeping it in specialized storage technologies, and making it accessible to specific analytically-inclined personnel. So why is it so difficult for companies to get huge benefits from all these analytical capabilities? The answer is that today’s enterprises have several of these environments, making searching for and analyzing data across these many instances a difficult, if not impossible, task.
The key solution is a comprehensive, easily created and accessed collection of metadata – an overarching “brain” that describes all aspects of the data found in these analytical stores, giving all users a comprehensive understanding of where the data resides, along with all its history.
This paper focuses on an important component of metadata, advanced data lineage. We discuss the many use cases for data lineage and stress the characteristics one should look for in mature data lineage technologies. The conclusion describes how organizations should begin their journey into solving their chaotic analytics environment by choosing a modern metadata management technology.
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