Are you leveraging your organizations most valuable data for your cloud analytics?
The rise of platforms such as Snowflake™, AWS, and Databricks® has given data analysts and engineers greater computing power and scale to make meaningful predictive analysis on larger data sets than ever before.
But output is only as good as the input, and your organization’s most valuable data is often locked away in your mainframe.
Join Bloor Research Analyst Daniel Howard, Software AG, and StreamSets as they explore:
- The latest trends in cloud data analytics
- The value (and challenges) of including enterprise mainframe data
- What criteria to use when selecting a data integration solution
- No-code options to modernize your mainframe data to be analytics-ready
|
|
 |
 |
||
|
Daniel Howard
Senior Research Analyst
Bloor Research
|
Mike Pickett
VP of Product Growth
StreamSets, a Software AG Company
|
Daniel Bierman
Principal Product Manager
CONNX, a Software AG Company
|
Schedule a Demo
See What Clients Are Saying About Us
Quality of Service and Fraud Protection
“RingCentral can now address quality of call service in real-time allowing us to make immediate adjustments to the network and carriers.”
Michael Becker Senior Director of Big Data, RingCentral
Quality of Service and Fraud Protection
“StreamSets technologies and DataOps practices allow us to deliver the business outcomes that we're focused on and make an impact on the people we serve every day.”
Anne-Britton Arnett VP, Information Management and Analytics, Humana
AI at Enterprise Scale
“StreamSets allows me to provide stable, sustainable data operations on top of both a self-service and professional platform and to operate this at scale.”
Dan Jeavons GM of Data Science, Shell