Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

CIO Business Intelligence

MARCH 9, 2022

However, they do contain effective data management, organization, and integrity capabilities. As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Warehouse, data lake convergence. Meet the data lakehouse.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

AWS Big Data

MAY 16, 2024

Because of this, many organizations are utilizing them as a support geography, aggregating their data to these grids to optimize both their storage and analysis. To learn more details about their benefits, see Introduction to Spatial Indexes. To learn more, visit CARTO.

Data Warehouse 103

Data Warehouse Visualization Cost-Benefit Optimization 103

O'Reilly on Data

OCTOBER 19, 2021

This introduces further requirements: The scale of operations is often two orders of magnitude larger than in the earlier data-centric environments. Not only is data larger, but models—deep learning models in particular—are much larger than before. However, none of these layers help with modeling and optimization.

IT 346

IT Testing Experimentation Software 346

IBM Big Data Hub

AUGUST 1, 2023

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. models are trained on IBM’s curated, enterprise-focused data lake. Foundation models focused on enterprise value IBM’s watsonx.ai

Modeling 59

Modeling Cost-Benefit Data Lake Machine Learning 59

CIO Business Intelligence

MARCH 22, 2022

Which type(s) of storage consolidation you use depends on the data you generate and collect. . One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Just starting out with analytics?

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

IBM Big Data Hub

MAY 9, 2023

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. A data store built on open lakehouse architecture, it runs both on premises and across multi-cloud environments.

Data Warehouse 109

Data Warehouse Cost-Benefit Machine Learning Modeling 109

Alation

APRIL 14, 2022

Pushing data to a data lake and assuming it is ready for use is shortsighted. Organizations launched initiatives to be “ data-driven ” (though we at Hired Brains Research prefer the term “data-aware”). It’s not a simple definition.

Metadata 59

Metadata Data Governance Modeling Data-driven 59