Systems | Development | Analytics | API | Testing

How to Extract Data from Fiserv Report Files and Write It to Excel

TL;DR: Fiserv platforms generate fixed-width.rpt files where every field sits at an exact character position. Astera ReportMiner maps those positions through a visual template editor, extracts the data, validates it against your business rules, and writes it directly to Excel, CSV, or 200+ other destinations. One template handles every future instance of the same report type, and the full pipeline runs unattended on a schedule.

How ReportMiner Processes Mainframe Reports at Enterprise Scale

Mainframe reports are one of the oldest and most persistent data extraction challenges in enterprise IT. They are generated by COBOL programs, printed by JES2/JES3 spoolers, and exported as fixed-width text files from IBM i Series, z/OS, AS/400, and similar systems. They power critical operations in banking, insurance, government, healthcare, and manufacturing. They also look nothing like the documents that modern AI extraction tools are designed for.

Katalon Product Roundup July 2026

July was an enterprise month. Most of what shipped answers the questions that come up once a test team grows past a handful of people: how do we hand documentation to an auditor, where is the evidence for this step, who changed this result and when, and how do we run the same suite against a feature branch without rebuilding the integration every time.

How to Automate Green Bar Report Extraction in Banking

If you work in banking operations, you know what a green bar report is. You probably have a stack of them arriving every morning: end-of-day balancing reports, settlement summaries, general ledger extracts, and transaction logs that run hundreds or thousands of pages. These reports are printed in fixed-width text with alternating green and white bands so someone with a highlighter can trace a number across 132 columns without losing their place.

Why Installing an npm Package Can Execute Code on Your Machine (And Why npm v12 Finally Changes That)

For years, the Node.js community has typed the same command billions of times: It's probably the most frequently executed command in the JavaScript ecosystem. We use it to start new projects, add dependencies, update existing ones, or simply bootstrap a development environment. It has become such a routine part of our workflow that most of us no longer stop to think about what actually happens during those few seconds while npm fills node_modules.

10 Best Accounts Payable Automation Software (2026)

Every AP team eventually asks the same question: not whether to automate - as PYMNTS reports, 78% of CFOs now see AI as central to accounts payable - but which platform actually fits their ERP, invoice volume, and team. We compared 10 AI-powered AP automation platforms on capability, integrations, and real user ratings, so you can skip the demo marathon and go straight to a shortlist.

BuyTheFans Social Media Services (SMM panel)

Buythefans SMM panel is a website where you can order social media engagement from one dashboard. The term is short for social media marketing panel. Instead of arranging separate campaigns, you choose a service, enter a target link and monitor the order centrally. The dashboard usually stores order status, quantity and payment details. For example, an Instagram profile URL identifies an account, while a YouTube video URL directs engagement to one upload. You still need to check every field carefully. A wrong or private link can delay fulfillment.

Safety and Design Tips for Low Voltage Distribution in Industrial Control Systems

Power Distribution is often an unsung but crucial element in maintaining a dependable and safe architecture of modern industrial automation systems. As reliable power is needed to drive motors and other heavy machinery, systems will often use high-voltage systems. Low Voltage (LV) Distribution, on the other hand, is used to power the "brain and nerve center" of the operation.

Flamegraphs Find It. Replay Proves It.

I made an API endpoint 13 times faster. Then I realized my first verification only checked the status, headers, and response schema. I had not checked the totals. I had made the bug faster. That is the problem with giving an AI coding agent one kind of evidence. A CPU profile can show where the application is slow, but not whether an optimization preserves behavior. A traffic replay can prove that behavior stayed stable, but not explain why the code burns CPU.