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Accelerating AI at scale without sacrificing security

CIO Business Intelligence

Above all, robust governance is essential. Failing to invest in data governance and security practices risks not only regulatory lapses and internal governance violations, but also bad outputs from AI that can stunt growth, lead to biased outcomes and inaccurate insights, and waste an organization’s resources.

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How companies are building sustainable AI and ML initiatives

O'Reilly on Data

In 2017, we published “ How Companies Are Putting AI to Work Through Deep Learning ,” a report based on a survey we ran aiming to help leaders better understand how organizations are applying AI through deep learning. Data scientists and data engineers are in demand.

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Why Data Governance Is Crucial for All Enterprise-Level Businesses

Cloudera

Whether the enterprise uses dozens or hundreds of data sources for multi-function analytics, all organizations can run into data governance issues. Bad data governance practices lead to data breaches, lawsuits, and regulatory fines — and no enterprise is immune. . Everyone Fails Data Governance.

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Deep automation in machine learning

O'Reilly on Data

If you suddenly see unexpected patterns in your social data, that may mean adversaries are attempting to poison your data sources. Anomaly detection may have originated in finance, but it is becoming a part of every data scientist’s toolkit. Tim Kraska on “How machine learning will accelerate data management systems”.

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Gartner Magic Quadrant for Metadata Management Includes Alation

Alation

Gartner predicts that “By 2020, 50% of information governance initiatives will be enacted with policies based on metadata alone.”. Magic Quadrant for Metadata Management Solutions , Guido de Simoni and Roxane Edjlali, August 10, 2017. Metadata management no longer refers to a static technical repository.

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Themes and Conferences per Pacoid, Episode 11

Domino Data Lab

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. A Program Synthesis Primer ” – Aws Albarghouthi (2017-04-24). Model-Driven Data Queries.

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All in the Data: Data Governance Bill of “Rights” Revisited

TDAN

I last published my Data Governance Bill of “Rights” in a TDAN.com article circa 2017. I mentioned in the earlier piece that Data Governance is all about doing the “right” thing when it comes to managing your data. It’s all in the data. That seems like a long time ago.