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Implementing Data Observability to Proactively Address Data Quality Issues

Dataversity

Unreliable or outdated data can have huge negative consequences for even the best-laid plans, especially if youre not aware there were issues with the data in the first place.

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IKEA’s Data Transformation: Lessons from a Global Giant

Timo Elliott

The Strategy: A Greenfield Approach IKEA adopted a greenfield strategy with SAP, rethinking its processes, technology, and data from the ground up. To create a connected, resilient ecosystem where data quality underpinned every operational decision. Establishing data frameworks and standards.

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6 Big Data Mistakes You Must Avoid At All Costs

Smart Data Collective

To help you identify and resolve these mistakes, we’ve put together this guide on the various big data mistakes that marketers tend to make. Big Data Mistakes You Must Avoid. Here are some common big data mistakes you must avoid to ensure that your campaigns aren’t affected. Ignoring Data Quality.

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Data Quality Best Practices to Discover the Hidden Potential of Dirty Data in Health Care

Dataversity

Health plans will […]. The post Data Quality Best Practices to Discover the Hidden Potential of Dirty Data in Health Care appeared first on DATAVERSITY.

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Why Data Quality Problems Plague Most Organizations (and What to Do About It)

Dataversity

Unfortunately, most organizations – across all industries – have Data Quality problems that are directly impacting their company’s performance. The post Why Data Quality Problems Plague Most Organizations (and What to Do About It) appeared first on DATAVERSITY.

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The Art and Science of FP&A Storytelling

Timo Elliott

I recently participated in a web seminar on the Art and Science of FP&A Storytelling, hosted by the founder and CEO of FP&A Research Larysa Melnychuk along with other guests Pasquale della Puca , part of the global finance team at Beckman Coulter and Angelica Ancira , Global Digital Planning Lead at PepsiCo. And finally, agility.

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What is Dark Data, Why Does it Matter, and Why Are Humans Still Needed?

Timo Elliott

Improving data quality. Unexamined and unused data is often of poor quality. Today’s data quality solutions, augmented by machine learning capabilities, can help sift through the noise, identify the patterns of bad data quality, and help fix the problem. Data augmentation.