Cloudera

SEPTEMBER 17, 2020

By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. . Our solution: Cloudera Data Visualization. This led them to fall behind.

Experimentation 83

Experimentation Data Warehouse Dashboards Visualization 83

AWS Big Data

JANUARY 9, 2024

Now users seek methods that allow them to get even more relevant results through semantic understanding or even search through image visual similarities instead of textual search of metadata. This functionality was initially released as experimental in OpenSearch Service version 2.4, Multi-modal search OpenSearch Service 2.11

Cost-Benefit 88

Cost-Benefit Visualization Modeling Machine Learning 88

Ontotext

JULY 6, 2023

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. internal metadata, industry ontologies, etc.) names, locations, brands, industry codes, etc.)

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

Octopai

OCTOBER 26, 2022

When DataOps principles are implemented within an organization, you see an increase in collaboration, experimentation, deployment speed and data quality. Did your data consumer just tell you about a visualization that she really could use in making an upcoming critical business decision? Let’s take a look. Six DataOps best practices.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

Sisense

JULY 24, 2019

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. There are many activities going on with AI today, from experimental to actual use cases. NLQ can serve both of those experiences using an analytic moment or an exploration mode.

Analytics 89

Analytics Experimentation Metadata Big Data 89

Domino Data Lab

JUNE 13, 2019

Visually examine the poorest matches, trying to understand what the MNIST authors could have done differently to justify these differences without at the same time changing the existing close matches. Start with a first reconstruction algorithm according to the information found in the [separate] paper introducing the MNIST dataset.

Testing 83

Testing Data Science Experimentation Metadata 83

Insight

MARCH 12, 2020

Data Collection The AIgent leverages book synopses and book metadata. To my knowledge, the most extensive repository of synopses and metadata is Goodreads. To collect these genre tags and other metadata, I took advantage of the well-documented Goodreads API. features) and metadata (i.e. In other words, if 0.1%

Modeling 59

Modeling Metadata Publishing Sales 59