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Data Quality vs Data Condition: The Power of Context

Anmut

Data without context is just meaningless noise, and any effort to improve or extract value from your data without considering the larger business context is doomed to fall short.? Unfortunately, traditional approaches to data remediation often focus on technical data quality in isolation from the broader data and business ecosystem.

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A steadfast community in an ever-changing data landscape

IBM Big Data Hub

Today, the Summer School has grown to include over 400 data leaders across 46 countries and nearly 25 industries. Storytelling remains a powerful tool in data strategy adoption. This year we’ve spoken with data leaders whose data strategies have stalled, resulting in falling confidence within their organizations.

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Improve Your Data’s Value With Data Governance

CDW Research Hub

What is your organization doing to protect the value of your data? A strong data governance strategy helps ensure that your data is usable, accessible and protected, guaranteeing trust in the quality and consistency of the data. But creating a data governance program is not something you can do overnight.

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AWS Lake Formation 2022 year in review

AWS Big Data

Data governance is increasingly top-of-mind for customers as they recognize data as one of their most important assets. Effective data governance enables better decision-making by improving data quality, reducing data management costs, and ensuring secure access to data for stakeholders.

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Why you should care about debugging machine learning models

O'Reilly on Data

Residual plots place input data and predictions into a two-dimensional visualization where influential outliers, data-quality problems, and other types of bugs often become plainly visible. That’s where remediation strategies come in. We discuss seven remediation strategies below. Data augmentation.

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The Rise of Unstructured Data

Cloudera

Since learning with labeled data is known as supervised learning, methods that reduce the need for labels have names such as self-supervision, semi-supervision, weak-supervision, non-supervision, incidental-supervision, few-shot learning, and zero-shot learning. Data curation.

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Insights from the 2019 DGIQ Conference

TDAN

The 2019 Data Governance and Information Quality (DGIQ) Conference ([link] hosted by Debtech International and DATAVERSITY, took place in San Diego, California from June 3-7, 2019 and this year’s event was another resounding success!