O'Reilly on Data

MARCH 31, 2020

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. You might have millions of short videos , with user ratings and limited metadata about the creators or content. O’Reilly Strata Data & AI Conference.

Management 332

Management Machine Learning Experimentation Metrics 332

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

Jet Global

MAY 1, 2023

According to a 2019 ESG survey , developers were able to customize analytics based on what was best for the applications instead of making design choices to work with existing tools and were able to offer products that improved average selling price (ASP)and/or order value, which increased by as much as 25 percent. addresses).

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52