CIO Business Intelligence
MARCH 24, 2023
Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets.
Domino Data Lab
JULY 22, 2019
Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.
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CIO Business Intelligence
JUNE 28, 2022
Philosophers and economists may argue about the quality of the metaphor, but there’s no doubt that organizing and analyzing data is a vital endeavor for any enterprise looking to deliver on the promise of data-driven decision-making. And to do so, a solid data management strategy is key.
Data Insight
JANUARY 21, 2020
Though we’re still in the early days of 5G, we expect to see improvements to latency and increased data volumes passing through the network in 2020 - more devices, more complex data capture… more, more, and more. Attracting and keeping great data science talent is another obstacle in itself.
CIO Business Intelligence
MAY 17, 2022
This incident, which provides insight into what can go wrong for any enterprise that has deployed AI without adequate data governance , is just the latest in a series of high-profile companies that have seen their AI-related PR disasters all over the front pages. We have very low confidence that our solutions are sufficient.”.
Cloudera
OCTOBER 1, 2022
While the word “data” has been common since the 1940s, managing data’s growth, current use, and regulation is a relatively new frontier. . Governments and enterprises are working hard today to figure out the structures and regulations needed around data collection and use. Infrastructure.
Cloudera
FEBRUARY 16, 2022
Each project consists of a declarative series of steps or operations that define the data science workflow. We can think of model lineage as the specific combination of data and transformations on that data that create a model. Each user associated with a project performs work via a session.
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