Sisense

AUGUST 28, 2020

Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is. What is data integrity?

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

Ontotext

DECEMBER 1, 2023

So, KGF 2023 proved to be a breath of fresh air for anyone interested in topics like data mesh and data fabric , knowledge graphs, text analysis , large language model (LLM) integrations, retrieval augmented generation (RAG), chatbots, semantic data integration , and ontology building.

Metadata 78

Metadata Sales Consulting Enterprise 78

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

CIO Business Intelligence

FEBRUARY 20, 2023

Benefits of Salesforce certifications Salesforce jobs range from the technical (architects, developers, implementation experts) to those related to marketing and sales. The certification emphasizes testing, governance, and integration with external systems within an organization’s infrastructure.

Consulting 72

Consulting B2B Cost-Benefit Sales 72

CIO Business Intelligence

NOVEMBER 29, 2022

Here, I’ll highlight the where and why of these important “data integration points” that are key determinants of success in an organization’s data and analytics strategy. Layering technology on the overall data architecture introduces more complexity. Data and cloud strategy must align.

Data Architecture 110

Data Architecture Data Integration IoT Strategy 110

Ontotext

JANUARY 10, 2024

Often, an enterprise starts with one thing it does well and then adds more business lines to expand the market. This requires new tools and new systems, which results in diverse and siloed data. And each of these gains requires data integration across business lines and divisions. We call this the Bad Data Tax.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

Cloudera

SEPTEMBER 7, 2023

Perhaps the biggest challenge of all is that AI solutions—with their complex, opaque models, and their appetite for large, diverse, high-quality datasets—tend to complicate the oversight, management, and assurance processes integral to data management and governance. Track market trends. Systematize governance.

Insurance 83

Insurance Risk Data-driven Finance 83