Remove Data Governance Remove Data Warehouse Remove Unstructured Data
article thumbnail

Domo Addresses Data Products and Agentic AI

David Menninger's Analyst Perspectives

Domo is best known as a business intelligence (BI) and analytics software provider, thanks to its functionality for visualization, reporting, data science and embedded analytics. Facilitating self-service data analytics was an early design goal for Domo, providing the company with differentiation compared to many of its rivals.

Metrics 130
article thumbnail

SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

In fact, by putting a single label like AI on all the steps of a data-driven business process, we have effectively not only blurred the process, but we have also blurred the particular characteristics that make each step separately distinct, uniquely critical, and ultimately dependent on specialized, specific technologies at each step.

Insiders

Sign Up for our Newsletter

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

article thumbnail

Data governance in the age of generative AI

AWS Big Data

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

article thumbnail

The DataOps Vendor Landscape, 2021

DataKitchen

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . QuerySurge – Continuously detect data issues in your delivery pipelines. Process Analytics. Meta-Orchestration .

Testing 304
article thumbnail

The Lakehouse Isn’t The End Game — Here’s What Comes Next

Data Virtualization

Reading Time: 2 minutes The data lakehouse has emerged as a powerful and popular data architecture, combining the scale of data lakes with the management features of data warehouses. It promises a unified platform for storing and analyzing structured and unstructured data, particularly for.

article thumbnail

3 things to get right with data management for gen AI projects

CIO Business Intelligence

Collect, filter, and categorize data The first is a series of processes — collecting, filtering, and categorizing data — that may take several months for KM or RAG models. Structured data is relatively easy, but the unstructured data, while much more difficult to categorize, is the most valuable.

article thumbnail

Get maximum value out of your cloud data warehouse with Amazon Redshift

AWS Big Data

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. However, these wide-ranging data types are typically stored in silos across multiple data stores.