Enterprise systems fail every 12 seconds across the globe. Companies lose millions when their data crashes or reports come back wrong. But at one big financial company in the Midwest, system breakdowns dropped 89% after they brought in someone who thinks about software like a mechanic thinks about engines. Most sectors, including healthcare, struggle with bad data. Every single data leader dealt with data quality problems in 2024. Banks and investment firms get hit hardest because regulators watch everything they do. The business intelligence market hit $31.98 billion last year and will jump to $63.20 billion by 2032 as more companies try to fix their data mess. Every single data leader dealt with data quality problems in 2024 business intelligence market hit $31.98 billion last year Kawaljeet Singh Chadha started as a Business Intelligence Analyst in January 2025. He works with their biggest client, helping them make sense of systems that were falling apart. Most analysts focus on reports and dashboards. He looks at why systems break before they even get turned on. The financial firm was drowning in problems. Old computer systems couldn't handle new rules from regulators. Business people would ask for changes, but by the time tech teams built them, nothing worked right. Projects took months longer than planned. Reports came back with wrong numbers. Everyone blamed everyone else. He teamed up with the firm's contact person to tackle the core problem. He takes what business people want and writes it down in a way that programmers understand. These Software Requirement Specification documents become the blueprint for everything that gets built. He also writes, changes, and runs all the databases and reports that keep the company running. His fix was simple but powerful. Test everything before it goes live. He creates test plans that check if systems do what they're supposed to do. He works with the team that installs software on servers, making sure everything connects properly in development, testing, and live environments. Most companies skip this step and pay for it later. He also manages when systems get updated or changed. Business processes get documented properly. Software and hardware are evaluated before purchase. The whole system architecture gets checked to make sure it can handle what the business needs. He looks for ways to make things work better and faster. "The key is making sure every requirement can be tested and verified before we deploy anything to production," Kawaljeet Singh Chadha says. "When you have clear test scenarios and proper data validation, you eliminate most of the issues that cause system failures down the line." Simple testing saves millions. His testing approach covers everything. Systems Acceptance Testing makes sure new software works. Functionality Testing checks individual pieces, how they connect, and whether updates break existing features. He sets up test environments, loads fake data that looks real, and helps business teams try everything out before launch. He also talks to software vendors to create tests that match how people use the systems. The results speak for themselves. System crashes dropped 89% in six months. Reports that used to be 73% accurate now hit 98%. New features that took 47 days to launch now take 12 days. Programmers spend 65% less time fixing broken code. The changes go beyond just technical wins. Business people trust that their requests will work when built. The compliance team meets regulatory deadlines without panic. Customer service reps help clients instead of dealing with broken systems all day. Healthcare Systems Learn From Finance The healthcare sector faces similar data integration challenges but with higher stakes. Kawaljeet Chadha’s recent research into Zero-Trust Data Architecture for multi-hospital systems shows how financial industry lessons apply to medical environments. Healthcare organizations struggle with Electronic Health Records, wearable device streams, and clinical trial data scattered across institutions. His zero-trust security models that verify every access request, enforce least-privilege permissions, and create micro-segmented networks solve these problems while meeting HIPAA requirements. Early implementations in oncology research demonstrate faster adverse-event detection and improved patient outcomes. Healthcare follows banking's path toward systematic data governance and bulletproof security frameworks. Better processes change everything He keeps looking for ways to make things run smoothly. He watches system performance and reports when things slow down or break. His recommendations for new features get implemented because they're based on real data. He creates development plans with actual deadlines that teams can meet. His work writing requirements, specifications, and business processes has changed how the company handles technology projects. No more guessing about what needs to be built. Everyone knows what they're getting before work starts. "We went from constantly firefighting system problems to having predictable, reliable infrastructure," Kawaljeet Singh Chadha explains. "When business rules are properly documented and tested, everyone knows what to expect from the systems." Banks finally get serious about data. This change reflects what's happening across the financial industry. Companies are tired of losing money to bad data and broken systems. Banks and investment firms need bulletproof systems because regulators fine them for mistakes. Customers expect their money information to be perfect. The companies that figure out reliable data and testing will have huge advantages over competitors still fighting system fires. Smart organizations now see that business intelligence starts with getting the basics right. Good requirements, thorough testing, and proper documentation create the foundation for advanced analytics. As data gets bigger and regulations get tougher, the systematic approach he uses becomes essential for staying competitive while avoiding regulatory trouble. Financial companies are finally embracing structured approaches to requirements and testing. The firms that invest in these fundamentals can handle growing data complexity while keeping the reliability that customers and regulators demand from financial institutions.

This story contains new, firsthand information uncovered by the writer.

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