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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.
It’s not just about fixing errors—the framework goes beyond cleaning data as it emphasizes preventing data quality issues throughout the data lifecycle. A data quality management framework is an important pillar of the overall data strategy and should be treated as such for effective datamanagement.
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 data governance strategy.
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