From SQL Bottlenecks to Self-Service Insights: A Case Study in NLP-Driven Data Access for a Pharma Giant

One-liner summary:
Ideas2IT partnered with a Fortune 500 pharmaceutical company to build an NLP-powered data access platform, allowing non-technical users to query enterprise data using natural language. The result: 2.5x faster decision-making and a significant reduction in IT dependency.

The Problem with the Status Quo

The client had a vast internal data ecosystem, but business teams struggled to access it.

Users couldn’t write SQL, BI dashboards were rigid, and nearly every data request required IT or analytics support. This created long lead times for even basic questions.

The outcome: delayed decisions, missed opportunities, and underutilized data assets.

The company needed a new interface to its data that is something fast, intuitive, and usable by non-technical roles.

Where the Gaps Were

Operational bottlenecks included:

  • High reliance on data teams for simple queries
  • Reporting cycles that spanned days or weeks
  • BI tools with steep learning curves for frontline users
  • Fragmented access to data sources
  • Missed decision windows due to insight delays

Dashboard access was the difficult are than the actual dashboard creation itself..

What We Delivered

Ideas2IT developed a zero-code decision support platform that lets business users ask questions in plain English and receive instant answers, complete with charts and tables, within seconds.

Key Capabilities and Architecture:

  • Natural Language Interface: Custom NLP models translated English queries into SQL
  • Dynamic Table Generator: Queried data was rendered automatically into structured, analysis-ready tables
  • Auto-Visualization Engine: Users could generate visualizations bar, line, pie on demand, without writing code
  • Seamless Integration: The platform connected securely to existing databases and BI tools for real-time access
  • Scalable, API-First Design: Containerized architecture ensured enterprise-grade performance and scalability

The system enabled data access at the speed of conversation without compromising governance or accuracy.

Outcomes We Achieved

Capability Impact
Time to insight Reduced by 60 percent through real-time natural language queries
Decision-making speed Increased 2.5x across business units
IT and analytics load Decreased as self-service adoption scaled
Data trust and literacy Improved through accurate, integrated results
Visualization agility Increased with instant chart creation, no BI tool dependency

Business teams could now explore data, answer questions, and make decisions—without waiting in dev queues or struggling through complex tools.

Industry
Pharma & Life Sciences
Location
USA
Tech Stacks
Challenge

Business users struggled to extract insights, relying heavily on IT to run reports and queries. This slowed decision-making and stalled response to market changes.

Key Takeaways

  • Speed matters. Insight latency erodes decision-making and market response
  • NLP is not UX. It's an unlock for business users to interact directly with data
  • Self-service demands trust. Accuracy, access control, and integration cannot be compromised
  • Freeing data teams changes the game. Less time on report generation means more time for strategic analytics

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