O'Reilly on Data

MARCH 31, 2020

You might have millions of short videos , with user ratings and limited metadata about the creators or content. Job postings have a much shorter relevant lifetime than movies, so content-based features and metadata about the company, skills, and education requirements will be more important in this case.

Management 332

Management Machine Learning Experimentation Metrics 332

erwin

DECEMBER 20, 2018

The driving factors behind data governance adoption vary. Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. The Top 6 Benefits of Data Governance.

Data Governance 40

Data Governance ROI Risk Management Metadata 40

O'Reilly on Data

MARCH 18, 2020

The new survey, which ran for a few weeks in December 2019, generated an enthusiastic 1,388 responses. This year, about 15% of respondent organizations are not doing anything with AI, down ~20% from our 2019 survey. It seems as if the experimental AI projects of 2019 have borne fruit. But what kind? Bottlenecks to AI adoption.

Enterprise 313

Enterprise Deep Learning Data Governance Risk 313

erwin

MARCH 4, 2021

Modern data governance is a strategic, ongoing and collaborative practice that enables organizations to discover and track their data, understand what it means within a business context, and maximize its security, quality and value. Virginia residents also would be able to opt out of data collection.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

Cloudera

AUGUST 4, 2021

Data governance used to be considered a “nice to have” function within an enterprise, but it didn’t receive serious attention until the sheer volume of business and personal data started taking off with the introduction of smartphones in the mid-2000s. This is essential to delivering data-driven insights.

Data Governance 82

Data Governance Metadata Data-driven Enterprise 82

Alation

FEBRUARY 8, 2022

In contrast to this common, centralized approach, a data mesh architecture calls for responsibilities to be distributed to the people closest to the data. Middlemen — data engineering or IT teams — can’t possibly possess all the expertise needed to serve up quality data to the growing range of data consumers who need it.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 52

Domino Data Lab

OCTOBER 9, 2019

We’ll examine National Oceanic and Atmospheric Administration (NOAA) data management practices which I learned about at their workshop, as a case study in how to handle data collection, dataset stewardship, quality control, analytics, and accountability when the stakes are especially high. Metadata Challenges.

Deep Learning 69

Deep Learning Metadata Machine Learning Data Science 69