The concerns on how to manage data quality and need for data documentation is increasing with the usage of data in various domains and various regulatory needs. According to a survey carried out by O’Reilly on the state of Data Quality in 2020, it was identified that even though there is attention given to data quality, organizations seem to lack the knowledge to address data quality concerns. It was recognized that key ingredients for data governance such as meta data management via data lineage and data provenance are missing within organizations. This analysis highlights the role data lineage plays in successful data governance strategy and the benefits.
A brief introduction to data governance.
Organizations are moving towards implementing data centric strategies for its business processes. Data governance is a core component of the data management strategy which can be a major turning point for today’s businesses. Data governance as the name suggests is when standards and policies are created for governing data in a business organization. Data governance assists organizations to have a better control over data, reduce inconsistencies and eliminate redundancies. For effective implementation there is a governing/ steering committee as well as data stewards within the organization. While there is attention paid for data stewards and for the steering team who work towards planning, implementing, and enforcing procedures, there is more to data governance. Data lineage is one such important methodology or a tool often overlooked which can be implemented to improve and trace data. It lets you know about the data you possess within the systems, the locations and how it is related between the systems. This also lets you know whether the implemented rules are in action.
What is data lineage?
Data lineage assists in tracing meta data and improving meta data management. This would in turn create a tracing mechanism and transparency over the data available within the organization for data governance. A data lineage tool may even assist in addressing poorly labeled or unlabeled data. Furthermore, Data lineage helps to document the alterations from origin to the destination. This is especially important as more regulations are…