Extract data from mainframe reports in retail operations
Reduce the effort of extracting and cleaning mainframe report data so retail teams can use it more quickly across analytics, reporting and downstream systems.
Retailers that rely on mainframes often face a stubborn data bottleneck: critical information is trapped in large, complex report files that are difficult to extract, cleanse and reuse consistently.
This fact sheet explores how automated and semi-automated workflows can help teams turn mainframe report data into trusted, analytics-ready information for use across BI, CRM, marketing and other downstream systems.
Download the fact sheet to see how a more repeatable, auditable approach can reduce manual effort, improve data quality and make legacy retail data more useful across the business.
Explore how to reduce the bottlenecks that keep mainframe data out of reach
- Learn how retailers can extract and cleanse data from large green bar reports and other complex file types more efficiently
- See how repeatable, auditable workflows can help improve consistency and reduce operational risk
- Explore how legacy mainframe data can be prepared for BI, CRM, marketing and other downstream systems
- Understand how visual, no-code workflow options can help business users work more effectively with complex data sources