Welcome to the May Issue of Mainframe Access Insights!
Unlocking AI’s Full Potential Starts with Your Data
The AI boom is only as powerful as the data behind it. Yet too often, enterprises find their most trusted and valuable data — stored on IBM Z in VSAM files, COBOL copybooks, DB2 tables, or SMF logs — locked away from the very platforms driving innovation.
At VirtualZ, we believe data access shouldn’t slow down transformation.
This month, we’re focused on how enterprises can unlock that data — securely, in real time, and without rewriting applications or building fragile pipelines. From AI-readiness with Vertex AI and SageMaker to JDBC-to-cloud integrations, we’re redefining what’s possible with no-code simplicity and speed.
Explore our latest innovations, join an upcoming masterclass, or catch up on demand with the new episode of the Skyward Data podcast.
Let’s make your data work harder — for your AI, your cloud, and your business.
Insights & Innovation
Modern AI depends on large volumes of timely, structured, and trusted data. Yet much of the information businesses rely on — from financial transactions to customer histories — is stored in enterprise systems that lack APIs, real-time integration points, or cloud compatibility.
Data remains:
- Stored in formats such as VSAM, COBOL copybooks, and DB2 tables
- Bound by strict compliance and governance requirements
The result? AI efforts stall, analysts are limited, and digital transformation lags behind.
While AI platforms like Google Vertex AI, Amazon SageMaker AI, Microsoft Azure Machine Learning (ML), and IBM watsonx offer powerful capabilities, they are only as effective as the data they can reach.
That’s where VirtualZ comes in.
With its patented, no-code solution PropelZ, VirtualZ enables near real-time, secure, and scalable access to data on IBM Z and enterprise platforms — without ETL, change data capture, or custom development.
Webinar Spotlight | Listen on Demand
Discover how VirtualZ enables seamless integration between IBM Z mainframes and GitHub, supporting version control, CI/CD pipelines, and modern DevOps workflows — all without disrupting legacy processes.
Key Topics
- Direct GitHub Repository Access: Enable mainframe applications to interact natively with GitHub for streamlined development.
- Accelerating AI-Driven Modernization: Leverage real-time data access to power AI-driven refactoring and migration with tools like GitHub Copilot.
- Reducing Costs and Breaking Down Silos: Eliminate the need for expensive ETL and replication processes while fostering collaboration between mainframe and modern development teams.
What Experts are Saying:
“Perhaps most challenging to conventional thinking is the company’s Zaac solution, which allows mainframe applications to use cloud storage as if it were native DASD (Direct Access Storage Device). This brings the kind of flexible storage options that distributed systems have enjoyed for years to the mainframe world, but without compromising on the platform’s renowned security and reliability characteristics.”
— Dale Vile, Co-founder, Freeform Dynamics
From the Blog: Must-Read Insights
PropelZ Expands to Support Any JDBC-Compatible Database as Input
With our latest expanded input capabilities, PropelZ can ingest data from virtually any database that supports JDBC (Java Database Connectivity) — making it a truly universal data integration solution.
Breaking the Boundaries of Mainframe-Centric Data Movement
With this new capability, PropelZ is no longer limited to just mainframe-hosted data sources. Organizations can now:
- Extract data from any JDBC-compatible database: including Oracle, MySQL, SQL Server, PostgreSQL, and cloud-based databases.
- Seamlessly move this data across platforms: whether it’s from an on-premises system to the cloud or between geographically distributed data centers.
- Leverage the same no-code transformation engine: ensuring format consistency, automated conversion, and schema alignment across both mainframe and non-mainframe data sources.
Summer Webinar Series
The AI-Ready Data Masterclass
Join us on June 3rd for a 30-minute session to see how to enable instant access to structured mainframe data — fueling AI, analytics, and cloud transformation.
AI models are only as powerful as the data behind them. And for many enterprises, that data still lives on IBM Z, but traditional tools make accessing it slow, expensive, and complex.
What You’ll Learn:
- How PropelZ, the no-code data platform from VirtualZ, enables integration with IBM watsonx, Google Vertex AI, Amazon SageMaker, and Azure ML
- How it delivers structured data from VSAM files, SMF logs, and COBOL copybooks
- How it enables secure, real-time data access — without disrupting source systems
Next in the Series: Fueling Your AI and Modernization Goals
- June 17: Mainframe to Cloud, Simplified
Move data from IBM Z to Snowflake, BigQuery and more — without code, scripts, or delays.
Register Now - July 8: Mainframe Data. Governed. Compliant. Cloud-Ready.
Send SMF logs, VSAM files, and more to Tableau, Power BI, and cloud data lakes — securely and policy-aligned.
Register Now - July 22: Your Database. Your Cloud. No Code.
Move data from DB2, IMS, IDMS, Datacom, and other JDBC sources — quickly and seamlessly to the cloud.
Register Now - August 5: From IBM Z to Observability — Simplified
Stream console messages, RACF logs, SMF records and more to Splunk, Elastic, Exabeam, or OpenTelemetry tools.
Register Now - August 19: Legacy Reports Out. Real-Time Dashboards In.
Turn static mainframe reports into real-time insights in Power BI, Tableau, and modern analytics tools.
Register Now
New Episode: Skyward Data Podcast
Join industry veterans Marc Sokol and Todd Henley for a fascinating journey through the evolution of data governance, from mainframe programming in the 1970s to today’s AI-powered enterprise systems.
Marc, with over four decades in technology, shares insights from his days writing COBOL compilers to his current role at VirtualZ, while Todd, founder at Paperkite.ai, brings his expertise as a former Chief Data Governance and Privacy Officer.
They explore how metadata serves as “the language of data governance” and discuss the critical challenges of implementing responsible AI in regulated industries. This episode offers invaluable perspectives on legacy system migrations, regulatory compliance, and the future of enterprise data management.
Skyward Data is THE podcast for professionals who want to gain a competitive edge in the evolving data landscape. Join us on your favorite platform, and subscribe to remain ahead of the competition.