Enabling New Reporting and Analytics Use Cases When Mainframe Data Access is Simplified
Mike Pickett, Vice President of Growth for StreamSets (now part of Software AG), talks about mainframe data access for reporting and analytics.
Topic: Analytics
How real-time data is used in business analytics, including predictive, descriptive, and prescriptive uses. Edge analytics is also explored.
Cloud’s Increasing Role in Supporting ESG Reporting
Data needed for ESG reporting must be easily available to the cloud services to assist in analysis. Smart data pipelines can
Real-time Analytics News for Week Ending May 20
In this week's real-time analytics news: SAP SE and its partners made multiple announcements at the SAP Sapphire conference.
Real-time Analytics News for Week Ending May 13
In this week's real-time analytics news: IBM used its IBM THINK conference to introduce IBM Event Automation, a solution that helps businesses become …
Predictive Intelligence Only Works With High Quality Data
Poor data quality leads to several other intangible losses such as customer dissatisfaction, less effective decision-making, and the reduced ability to execute …
Only 44% of Analytics Teams Provide Value
Some of the main roadblocks to providing effective value include skill and staff shortages, lack of resources or funding, and cultural challenges.
Real-time Analytics News for Week Ending May 6
In this week's real-time analytics news: The NSF, several other federal agencies, higher education institutions, and other stakeholders will invest $140 …
The Technology Behind and Benefits of Data Pipeline Automation
A chat with Sean Knapp, founder and CEO of Ascend.io, about the challenges businesses face with data pipelines and how data pipeline automation can
How OEMS Reduce Warranty Costs Using Connected Vehicle Data
Given its distinct advantages, it’s a safe bet to assume that the connected vehicle will drive significant new cost optimization and revenue-enhancing …
DataOps’ Role in a Modern Data Pipeline Strategy
Increasingly, businesses are using DataOps principles to guide their data pipeline strategies, construction, and operations.