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

datapine

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.

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Common Business Intelligence Challenges Facing Entrepreneurs

datapine

Data analytics isn’t just for the Big Guys anymore; it’s accessible to ventures, organizations, and businesses of all shapes, sizes, and sectors. The power of data analytics and business intelligence is universal. Entrepreneurs And Business Intelligence Challenges. Let’s get started!

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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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Getinge’s digital transformation shows scaling and adapting in equal measure

CIO Business Intelligence

There’s been good progress but, admittedly, there’s still a lot of work to do, says Nilsson, since it’s difficult to take ownership in a large organization and streamline data management. In the long run, we envisage new services such as being able to handle predictive maintenance based on what we know about the products,” he says.

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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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Finding Data Quality

Jim Harris

Have you ever experienced that sinking feeling, where you sense if you don’t find data quality, then data quality will find you? I hope that you enjoy reading this blog post, but most important, I hope you always remember: “Data are friends, not food.” Data Silos. You, Data-Dude, takin’ on the defects.

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Putting the Business back into Business Intelligence: reduce Data Debt by reconciling IT Department with Finance Professionals

Jen Stirrup

What is Data Debt? Data debt is like technical debt, only visible in bad data, poor data quality, and an underuse of data-oriented technology to help make better decisions. Instead, it simply gets absorbed into the business processes and it becomes part of everyday work.