Data Lakes were originally constructed to address advanced analytics by providing vast arrays of structured and unstructured data for data scientists and their peers to mine. More recently, however, they are being used to address many other use cases such as traditional Business Intelligence and ad hoc reporting. While they were originally thought of as storage platforms for ‘Big Data’ i.e. unstructured and semi-structured datasets, they are now being used to also store more traditional structured data. As companies move this data into the Data Lake, Data Governance becomes imperative to address needs such as understanding the meaning and lineage of the data, ensuring that the data is suitable for business purpose and obeys regulations such as GDPR, HIPAA and CCPA, and ensuring that restrictions to access and contractual terms are met. Data Governance in the Lake (DGITL) lays out some aspects of this Governance which are relevant whether companies have successful Enterprise Data Governance programs or not.
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