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If storage costs are escalating in a particular area, you may have found a good source of dark data. If you’ve been properly managing your metadata as part of a broader datagovernance policy, you can use metadata management explorers to reveal silos of dark data in your landscape. Data sense-making.
Your analysts, data scientists, data engineers, and machine learning engineers will offer unique viewpoints and preferences, and should all be brought into the conversation as experts in their areas of the business. The data lakehouse is one such architecture—with “lake” from data lake and “house” from datawarehouse.
Your analysts, data scientists, data engineers, and machine learning engineers will offer unique viewpoints and preferences, and should all be brought into the conversation as experts in their areas of the business. The data lakehouse is one such architecture—with “lake” from data lake and “house” from datawarehouse.
As important as it is to know what a data quality framework is, it’s equally important to understand what it isn’t: It’s not a standalone concept—the framework integrates with datagovernance, security, and integration practices to create a holistic data ecosystem.
Employ a ChiefDataOfficer (CDO). Big data guru Bernard Marr wrote about The Rise of ChiefDataOfficers. This should also include creating a plan for data storage services. Are the data sources going to remain disparate? For this purpose, you can think about a datagovernance strategy.
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