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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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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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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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Top 10 Reasons for Alation with Snowflake: Reduce Risk with Active Data Governance

Alation

In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. So why are organizations not able to scale governance? Meet Governance Requirements.

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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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10 ways to break free from AI pilot purgatory

CIO Business Intelligence

These 10 strategies cover every critical aspect, from data integrity and development speed, to team expertise and executive buy-in. Data done right Neglect data quality and you’re doomed. It’s simple: your AI is only as good as the data it learns from. Big data is seductive, but more isn’t better if it’s garbage.

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Making your AI work with Data Observability: Trends in 2024 and beyond

Jen Stirrup

Data observability solutions empower organizations to gain clear visibility into their data pipelines, rising to meet the growing requirement that data is correct, timely, and dependable. Data observability includes several concepts, and here are some examples: Data Freshness : How up-to-date is the data?