Jen Stirrup

MARCH 29, 2023

SAP helps to solve this search problem by offering ways to simplify business data with a solid data foundation that powers SAP Datasphere. It fits neatly with the renewed interest in data architecture, particularly data fabric architecture. They fail to get a grip on their data.

Metadata 121

Metadata Data Warehouse Data Integration Business Intelligence 121

Ontotext

DECEMBER 1, 2023

Atanas Kiryakov presenting at KGF 2023 about Where Shall and Enterprise Start their Knowledge Graph Journey Only data integration through semantic metadata can drive business efficiency as “it’s the glue that turns knowledge graphs into hubs of metadata and content”.

Metadata 78

Metadata Sales Consulting Enterprise 78

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Data providers and consumers are the two fundamental users of a CDH dataset.

Dashboards 95

Dashboards Analytics Metadata Data Warehouse 95

AWS Big Data

DECEMBER 21, 2023

Overview of solution As a data-driven company, smava relies on the AWS Cloud to power their analytics use cases. smava ingests data from various external and internal data sources into a landing stage on the data lake based on Amazon Simple Storage Service (Amazon S3).

Data Lake 89

Data Lake Data Warehouse Data-driven B2B 89

IBM Big Data Hub

AUGUST 4, 2023

Data democratization, much like the term digital transformation five years ago, has become a popular buzzword throughout organizations, from IT departments to the C-suite. It’s often described as a way to simply increase data access, but the transition is about far more than that.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

CIO Business Intelligence

AUGUST 3, 2023

In the past, First Service Credit Union’s Chief data officer Ty Robbins struggled to integrate data from the legacy, non-relational, and often proprietary tabular databases on which many credit unions run. Start early The time to standardize everything from data modeling to its security is when the data is acquired. “We

Analytics 86

Analytics Data Lake Metadata Cost-Benefit 86