Artificial Intelligence
5 Data Governance Tips: Don't Let Your "Data Lake" Turn Into a "Data Swamp"
Frits Korthals Altes of Turner sees many organizations starting to use “data lakes,” which make virtually all of an organization’s data accessible. But without proper data governance, you can quickly get overwhelmed by the data. He offers five tips to keep your “data lake” from turning into a “data swamp.”
How to Keep Your “Data Lake” from Overwhelming You
The availability of enormous amounts of data is one of the driving forces behind the rise of Artificial Intelligence (AI). Think of interactions with customers, patients, or students; purchases, transactions, or records; financial data; and process data. Many organizations are working on “data lakes” where data from every nook and cranny of the company or institution is brought together.
Not a swamp
However, centralized data storage alone does not provide a solid foundation for AI initiatives. In addition to this “raw” data, you also need metadata: What does the data describe? Where does the data come from? How was it generated? What processing has been applied to it? Without this metadata, your “data lake” can quickly turn into a “data swamp”: a massive amount of data that you can’t actually put to meaningful use.
Roundtable Discussion on Thursday, November 19
Data Governance
To make data usable and accessible, you need to effectively manage the data lifecycle. We call this Data Governance. For many organizations, this is a new area that needs to be developed. How do you set it up? How far should you go in managing your data? What steps need to be taken?
These five tips will help you keep your “data lake” from becoming a “data swamp”:
- Set up your data governance organization based on three core elements:
- Appoint a Data Management Manager (DMM) who has ultimate responsibility and sufficient authority and influence to make decisions regarding data management.
- Appoint a Data Steward for each domain, who is responsible for implementing data management within a specific domain. Within the domain, the Data Steward is an expert who understands the processes and systems and knows when changes to them are planned—or necessary. Data related to customer contact simply has a different dynamic and context than invoices and payments.
- A consultation framework in which Data Stewards share their experiences and challenges, and the Data Management Manager makes decisions and sets priorities
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