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The state of data quality in 2020

O'Reilly on Data

They don’t have the resources they need to clean up data quality problems. The building blocks of data governance are often lacking within organizations. These include the basics, such as metadata creation and management, data provenance, data lineage, and other essentials. And that’s just the beginning.

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Doing Cloud Migration and Data Governance Right the First Time

erwin

No less daunting, your next step is to re-point or even re-platform your data movement processes. And you can’t risk false starts or delayed ROI that reduces the confidence of the business and taint this transformational initiative. Why You Need Cloud Data Governance. GDPR, CCPA, HIPAA, SOX, PIC DSS).

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Automating Data Governance

erwin

Automating data governance is key to addressing the exponentially growing volume and variety of data. Data readiness is everything. Data readiness depends on automation to create the data pipeline. We asked participants to “talk to us about data value chain bottlenecks.”

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Four Use Cases Proving the Benefits of Metadata-Driven Automation

erwin

Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. The volume and variety of data has snowballed, and so has its velocity. As such, traditional – and mostly manual – processes associated with data management and data governance have broken down.

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Enhance data governance with enforced metadata rules in Amazon DataZone

AWS Big Data

We’re excited to announce a new feature in Amazon DataZone that offers enhanced metadata governance for your subscription approval process. With this update, domain owners can define and enforce metadata requirements for data consumers when they request access to data assets.

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When is data too clean to be useful for enterprise AI?

CIO Business Intelligence

Good data governance has always involved dealing with errors and inconsistencies in datasets, as well as indexing and classifying that structured data by removing duplicates, correcting typos, standardizing and validating the format and type of data, and augmenting incomplete information or detecting unusual and impossible variations in the data.

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There’s More to erwin Data Governance Automation Than Meets the AI

erwin

Prashant Parikh, erwin’s Senior Vice President of Software Engineering, talks about erwin’s vision to automate every aspect of the data governance journey to increase speed to insights. Although AI and ML are massive fields with tremendous value, erwin’s approach to data governance automation is much broader.