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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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Data-Driven Companies Leverage OCR for Optimal Data Quality

Smart Data Collective

OCR is the latest new technology that data-driven companies are leveraging to extract data more effectively. There are a number of benefits of using it to your company’s advantage. OCR and Other Data Extraction Tools Have Promising ROIs for Brands. Big data is changing the state of modern business.

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A summary of Gartner’s recent DataOps-driven data engineering best practices article

DataKitchen

On 24 January 2023, Gartner released the article “ 5 Ways to Enhance Your Data Engineering Practices.” Or, as one of our customers put it, “How do I increase the total amount of team insight generated without continually adding more staff (and cost)?” Staff turnover, stress, and unhappiness. It’s not been going well.

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Application modernization overview

IBM Big Data Hub

Application modernization starts with assessment of current legacy applications, data and infrastructure and applying the right modernization strategy (rehost, re-platform, refactor or rebuild) to achieve the desired result. Duplicative capabilities across applications and channels give rise to duplicative IT resources (e.g.,

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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

Third, any commitment to a disruptive technology (including data-intensive and AI implementations) must start with a business strategy. 3) How do we get started, when, who will be involved, and what are the targeted benefits, results, outcomes, and consequences (including risks)?

Strategy 290
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3 key digital transformation priorities for 2024

CIO Business Intelligence

After all, every department is pressured to drive efficiencies and is clamoring for automation, data capabilities, and improvements in employee experiences, some of which could be addressed with generative AI. Meanwhile, CIOs must still reduce technical debt, modernize applications, and get cloud costs under control.

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Top 6 Benefits of Automating End-to-End Data Lineage

erwin

Replace manual and recurring tasks for fast, reliable data lineage and overall data governance. It’s paramount that organizations understand the benefits of automating end-to-end data lineage. The importance of end-to-end data lineage is widely understood and ignoring it is risky business.