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Why Data Quality and Data Governance are Important to Achieve Compliance

Analysts Corner

In this article, we present a brief overview of compliance and regulations, discuss the cost of non-compliance and some related statistics, and the role data quality and data governance play in achieving compliance. The average cost of a data breach among organizations surveyed reached $4.24

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Mind the Gap: Data Quality Is Not “Fit for Purpose”

Dataversity

Welcome to the latest edition of Mind the Gap, a monthly column exploring practical approaches for improving data understanding and data utilization (and whatever else seems interesting enough to share). Last month, we explored the rise of the data product. This month, we’ll look at data quality vs. data fitness.

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Implementing a Business Glossary in Data Governance

Dataversity

A business glossary is a list of data-related terms and definitions, displayed clearly and logically so everyone in an organization can access them. A business glossary is an essential Data Literacy tool and crucial for effective Data Governance. Click to learn more about author Sharad Varshney.

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Data Synchronization: Definition, Tips, Myths, and Best Practices

Dataversity

It helps maintain consistency across disparate systems, enhancing data reliability and improving decision-making. So, to get started with […] The post Data Synchronization: Definition, Tips, Myths, and Best Practices appeared first on DATAVERSITY.

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Crucial Advantages of Investing in Big Data Management Solutions

Smart Data Collective

Big data management increases the reliability of your data. Big data management has many benefits. One of the most important is that it helps to increase the reliability of your data. Data quality issues can arise from a variety of sources, including: Duplicate records Missing records Incorrect data.

Big Data 291
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How Data Governance Drives Successful Business Results

Domo

The Data Governance Institute (DGI) defines data governance as “a system of decision rights and accountabilities for information-related purposes, executed according to agreed-upon models that describe who can take what actions with what information, and when, under what circumstances, using what methods.” Definitely.

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

Data Pine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data.