Mainframe Data for Cloud Analytics
Include mainframe data in your cloud analytics efforts easily and securely.
Easy and Intuitive Access to Mainframe Data
An increasing number of organizations are realizing data found in their mainframe systems can provide the next level insight to increase sales, improve operations, identify fraud, improve reporting and more. StreamSets Mainframe Collector is the only solution that captures data through a lightweight listener to avoid high additional costs, fits into and extends existing security policies, and presents data in a relational format so that users can easily understand and include the data in their cloud analytics efforts.
Liberate Your Mainframe Data
To Any Cloud Data Platform Including, AWS, Azure, Google, Snowflake and Databricks
What Does This Mean for You?
Improve Reporting and Analytics Efforts by Including More Strategic Data
A more efficient and secure way to bring mainframe and legacy data into your cloud data warehouse or data lake. Empower any user (Analysts, Customers, Suppliers…) with self service access to the data they’re authorized to use. Accelerate strategic data initiatives.
Identify and Include Strategic Data Sources and Cloud Destinations, and Build/Monitor Pipelines Accordingly
Mainframe and non-relational data sources (Adabas, IMS, VSAM, RMS) can be difficult to access and integrate data for consumption in modern platforms. This often means time consuming delays with data extracts or simply no access at all.
Ensure Uptime, Efficiency, and Reliability in Mainframe Design
Rely on a solution that provides minimal to no system disruption. Minimize new usage peaks and keep costs under control.
Adapt to and Extend Existing Security Policies and Governance Frameworks
Alternative approaches often require changes that require changing or updating existing security and governance frameworks which increases complexity and introduces new risks. Rely on a solution that maintains data security and governance standards.
