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What is data governance? Best practices for managing data assets

CIO Business Intelligence

Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets.

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What is BCBS 239 Compliance?

Octopai

It will not surprise you to learn all 11 of the bank-relevant principles are related to data in some form or fashion. Here’s a sampling: – Principle 1 covers data governance, including “a firm’s policies on data confidentiality, integrity, and availability, as well as risk-management policies.”.

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What is Data Lineage? Top 5 Benefits of Data Lineage

erwin

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (API)s, file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.

Metadata 111
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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

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Information Governance – The Secret to Monetizing Data

Grooper

Lack of competitiveness or business losses seem to be the main drivers to becoming more proactive with data governance and management. What you’re shooting for is enterprise-wide information governance. Responsibility for managing your company’s data must be clearly defined and supported.

Metrics 59
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The art and science of data product portfolio management

AWS Big Data

In the same way, overly restrictive data governance practices that either prevent data products from taking root at all, or pare them back too aggressively (deforestation), can over time create “data deserts” that drive both the producers and consumers of data within an organization to look elsewhere for their data needs.