Remove 2017 Remove Big Data Remove Metadata Remove Visualization
article thumbnail

5 Hardware Accelerators Every Data Scientist Should Leverage

Smart Data Collective

Although SageMaker has become a popular hardware accelerator since it was launched in 2017, there are plenty of other overlooked hardware accelerators on the market. If you want to streamline various parts of the data science development process, then you should be aware of all of your options. Neptune.ai. Neptune.AI

article thumbnail

AI in Analytics: The NLQ Use Case

Sisense

NLQ serves those users who are in a rush, or who lack the skills or permissions to model their data using visualization tools or code editors. So if we think about data access as a function of technical skills and the time it takes to get an answer, NLQ will be the first technology that users will turn to when looking for insights.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). We keep feeding the monster data. the flywheel effect.

article thumbnail

Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

He’s been out of Wolfram for a while and writing exquisite science books including Elements: A Visual Explanation of Every Known Atom in the Universe and Molecules: The Architecture of Everything. The gist is, leveraging metadata about research datasets, projects, publications, etc., Rinse, lather, repeat—probably each week.

article thumbnail

The year of the data catalog

Alation

Gartner: Magic Quadrant for Metadata Management Solutions. Magic Quadrant for Metadata Management Solutions 4 based on its ability to execute and completeness of vision. Today, metadata management has become a critical business driver as data leaders seek to govern and maximize the value from the influx of data at their disposal.