Remove Data Collection Remove Data Governance Remove Data Quality Remove Publishing
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3 powerful lessons of using data governance frameworks

CIO Business Intelligence

The first published data governance framework was the work of Gwen Thomas, who founded the Data Governance Institute (DGI) and put her opus online in 2003. They already had a technical plan in place, and I helped them find the right size and structure of an accompanying data governance program.

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5 Ways Data Engineers Can Support Data Governance

Alation

These data requirements could be satisfied with a strong data governance strategy. Governance can — and should — be the responsibility of every data user, though how that’s achieved will depend on the role within the organization. How can data engineers address these challenges directly?

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The Role of Data Governance During A Pandemic

Anmut

Data governance - who's counting? The role of data governance. This large gap between reported figures raises tough questions on the reliability of COVID-19 tracking data. In dealing with situations like pandemic data, how important are aspects of data governance such as standardised definitions?

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Data Mesh 101: How Data Mesh Can Be Used in an Organization

Ontotext

Domain teams should continually monitor for data errors with data validation checks and incorporate data lineage to track usage. Establish and enforce data governance by ensuring all data used is accurate, complete, and compliant with regulations.

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What is Data Mesh?

Ontotext

Data mesh solves this by promoting data autonomy, allowing users to make decisions about domains without a centralized gatekeeper. It also improves development velocity with better data governance and access with improved data quality aligned with business needs.

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5 Types of Costly Data Waste and How to Avoid Them

CIO Business Intelligence

Lowering the entry cost by re-using data and infrastructure already in place for other projects makes trying many different approaches feasible. Fortunately, learning-based projects typically use data collected for other purposes. . And the problem is not just a matter of too many copies of data.

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Data Science, Past & Future

Domino Data Lab

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.