Remove Data Governance Remove Data Integration Remove Data Quality Remove Optimization
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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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Data architecture strategy for data quality

IBM Big Data Hub

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

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

CIO Business Intelligence

Despite soundings on this from leading thinkers such as Andrew Ng , the AI community remains largely oblivious to the important data management capabilities, practices, and – importantly – the tools that ensure the success of AI development and deployment. Further, data management activities don’t end once the AI model has been developed.

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4 Common Data Integrity Issues and How to Solve Them

Octopai

It’s also a critical trait for the data assets of your dreams. What is data with integrity? Data integrity is the extent to which you can rely on a given set of data for use in decision-making. Where can data integrity fall short? Too much or too little access to data systems.

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Saving Data Costs with Data Lineage

Octopai

Here are some common cost areas where data lineage can be beneficial: Infrastructure and storage costs: Data lineage allows organizations to understand data usage patterns, access frequencies, and data dependencies. Data quality costs: Poor data quality can result in significant costs for organizations.

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8 data strategy mistakes to avoid

CIO Business Intelligence

At Vanguard, “data and analytics enable us to fulfill on our mission to provide investors with the best chance for investment success by enabling us to glean actionable insights to drive personalized client experiences, scale advice, optimize investment and business operations, and reduce risk,” Swann says.

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Sure, Trust Your Data… Until It Breaks Everything: How Automated Data Lineage Saves the Day

Octopai

By doing so, they aimed to drive innovation, optimize operations, and enhance patient care. They invested heavily in data infrastructure and hired a talented team of data scientists and analysts. This visibility was crucial for identifying and rectifying data quality issues quickly, ensuring consistent and reliable insights.

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