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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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Are you struggling to get started with Data Quality?   Interview with IQ International

Corinium

We are pleased to be working with our media partner, IQ International on our Chief Data & Analytics Officer Brisbane event, where they will be sharing some of their work in developing best practice data quality metrics for every industry. We will be joined by Dan Myers (USA), President at IQ International.

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Drug Launch Case Study: Amazing Efficiency Using DataOps

DataKitchen

data engineers delivered over 100 lines of code and 1.5 data quality tests every day to support a cast of analysts and customers. The team used DataKitchen’s DataOps Automation Software, which provided one place to collaborate and orchestrate source code, data quality, and deliver features into production.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality.

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Supply Chain Planning Maturity – How Do You Compare to Peers?

An event upstream in a different country or region can cause considerable disruption downstream. Time allocated to data collection: Data quality is a considerable pain point. How much time do teams spend on data vs. creative decision-making and discussion? Today's supply chains are networked, global ecosystems.

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Set up alerts and orchestrate data quality rules with AWS Glue Data Quality

AWS Big Data

Alerts and notifications play a crucial role in maintaining data quality because they facilitate prompt and efficient responses to any data quality issues that may arise within a dataset. This proactive approach helps mitigate the risk of making decisions based on inaccurate information.

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM).