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Data lineage is generally defined as a kind of data life cycle that includes the data's origins and where it moves over time. This term can also describe what happens to data as it goes through diverse processes. Data lineage can help with efforts to analyze how information is used and to track key bits of information that serve a particular purpose.
One common application of data lineage methodologies is in the field of business intelligence, which involves gathering data and building conclusions from that data. Data lineage helps to show, for example, how sales information has been collected and what role it could play in new or improved processes that put the data through additional flow charts within a business or organization. All of this is part of a more effective use of the information that businesses or other parties have obtained.
Another use of data lineage, as pointed out by business experts, is in safeguarding data and reducing risk. By collecting large amounts of data, businesses and organizations are exposing themselves to certain legal or business liabilities. These relate to any possible security breach and exposure of sensitive data. Using data lineage techniques can help data managers handle data better and avoid some of the liability associated with not knowing where data is at a given stage in a process.