Artificial intelligence and advanced analytics are transforming industries, but many organizations struggle to fully leverage the valuable data stored in their mainframes. These systems hold decades of critical business transactions, customer records, and operational insights—but without seamless integration, that data remains untapped.
The whitepaper, "Rethinking the Role of Mainframe Data in Enterprise AI and Analytics," explores how businesses are overcoming these challenges to unlock real-time insights, improve efficiency, and drive smarter decision-making.
By integrating mainframe data with hybrid cloud data in AI and analytics platforms, businesses can:
of leaders are actively pursuing AI to advance data and analytcis initiatives
of leaders said they found accessing mainframe data and contextual metadata to be challenging
Source: Survey conducted by Foundry and Rocket Software in May 2024.
While 92% of organizations are actively investing in AI-driven analytics, many still struggle to integrate mainframe data.
Common barriers include:
Rocket® DataEdge empowers businesses to realize greater business value from their AI, analytics, and corporate initiatives, enabling future innovation. By combining powerful data intelligence, data replication and sync, and data virtualization capabilities, Rocket DataEdge can manage and integrate even the most complex data environments.
The whitepaper "Rethinking the Role of Mainframe Data in Enterprise AI and Analytics" talks about how businesses are approaching AI adoption, the challenges they face, and strategies for integrating mainframe data into modern analytics platforms.
Read the whitepaper now to explore industry trends, real-world use cases, and best practices for unlocking the full potential of your mainframe data.
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