Cloudera

JUNE 11, 2024

More than two-thirds of companies are currently using Generative AI (GenAI) models, such as large language models (LLMs), which can understand and generate human-like text, images, video, music, and even code. However, the true power of these models lies in their ability to adapt to an enterprise’s unique context.

Enterprise 55

Enterprise Unstructured Data Contextual Data Data-driven 55

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 77

Data Science Data Analytics Prescriptive Analytics Analytics 77

Jet Global

APRIL 2, 2019

Many of the features frequently attributed to AI in business, such as automation, analytics, and data modeling aren’t actually features of AI at all. Which problems do disparate data points speak to? Enter data warehousing.

Enterprise 80

Enterprise OLAP Business Intelligence Internet of Things 80

IBM Big Data Hub

DECEMBER 16, 2022

It uses metadata and data management tools to organize all data assets within your organization. It synthesizes the information across your data ecosystem—from data lakes, data warehouses, and other data repositories—to empower authorized users to search for and access business-ready data for their projects and initiatives.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Jet Global

AUGUST 14, 2019

Which problems do disparate data points speak to? And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing.

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

Jet Global

OCTOBER 2, 2019

Which problems do disparate data points speak to? And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing.

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

O'Reilly on Data

OCTOBER 19, 2021

Let’s start by considering the job of a non-ML software engineer: writing traditional software deals with well-defined, narrowly-scoped inputs, which the engineer can exhaustively and cleanly model in the code. Not only is data larger, but models—deep learning models in particular—are much larger than before.

IT 351

IT Testing Experimentation Software 351