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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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Best BI Tools Examples for 2024: Business Intelligence Software

FineReport

Evolving BI Tools in 2024 Significance of Business Intelligence In 2024, the role of business intelligence software tools is more crucial than ever, with businesses increasingly relying on data analysis for informed decision-making.

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Dow CDO Chris Bruman: We needed a new approach to data quality

CIO Business Intelligence

Last year, Dow took a bold step to make better use of its data. With a goal of eliminating isolated islands of data and making better use of business intelligence as an enterprise asset, the company launched an internal organization that seamlessly integrated IT and the company’s global business units under one umbrella.

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IBM Loves DataOps

DataKitchen

Data is unique in many respects, such as data quality, which is key in a data monetization strategy. Data governance is necessary in the enforcement of Data Privacy. Automation and orchestration in an interoperable hybrid cloud distributed data landscape is where DataOps excels.

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Don’t Fear Artificial Intelligence; Embrace it Through Data Governance

CIO Business Intelligence

Software development, once solely the domain of human programmers, is now increasingly the by-product of data being carefully selected, ingested, and analysed by machine learning (ML) systems in a recurrent cycle. Further, data management activities don’t end once the AI model has been developed. era is upon us.

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5 Ways Data Engineers Can Support Data Governance

Alation

That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. How can data engineers address these challenges directly?

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The state of data quality in 2020

O'Reilly on Data

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Data quality might get worse before it gets better.