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Being Data-Driven Means Embracing Data Quality and Consistency Through Data Governance

Dataversity

The post Being Data-Driven Means Embracing Data Quality and Consistency Through Data Governance appeared first on DATAVERSITY. They want to improve their decision making, shifting the process to be more quantitative and less based on gut and experience.

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Good Data Quality Is the Secret to Successful GenAI Implementation

Dataversity

So why are many technology leaders attempting to adopt GenAI technologies before ensuring their data quality can be trusted? Reliable and consistent data is the bedrock of a successful AI strategy.

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How to Improve Data Quality by Using Feedback Loops

Dataversity

In this blog, we will take a look at: The impact poor Data Quality has on organizations and practical advice for how to overcome this challenge through the use of feedback loops. Poor Data Quality can cost organizations millions each year. Click to learn more about author Eva Murray.

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The Cool Kids Corner: Data Quality Is Not a Fish You Can Catch 

Dataversity

This is my monthly check-in to share with you the people and ideas I encounter as a data evangelist with DATAVERSITY. This month we’re talking about Data Quality (DQ). Read last month’s column here.)

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Data Quality Dimensions Are Crucial for AI

Dataversity

Since the data from such processes is growing, data controls may not be strong enough to ensure the data is qualitative. That’s where Data Quality dimensions come into play. […]. The post Data Quality Dimensions Are Crucial for AI appeared first on DATAVERSITY.

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How to Implement a Data Quality Framework

Dataversity

They have the data they need, but due to the presence of intolerable defects, they cannot use it as needed. These defects – also called Data Quality issues – must be fetched and fixed so that data can be used for successful business […].

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5 Common Data Governance Challenges (and How to Overcome Them)

Dataversity

It’s common for enterprises to run into challenges such as lack of data visibility, problems with data security, and low Data Quality. But despite the dangers of poor data ethics and management, many enterprises are failing to take the steps they need to ensure quality Data Governance.