Smart Data helped a Kentucky-based pharmaceutical services company enhance their technical platform by resolving systemic data quality issues, modernizing documentation, improving onboarding processes, and laying the foundation for scalable, monitored data governance.
Client
Pharmaceutical Services Provider
Industry
Healthcare
Timeline
2022 - Present
Project Overview
The client, a fast-scaling pharmaceutical services provider, faced significant operational inefficiencies due to lost onboarding processes, unclear technical documentation, and systemic data quality problems. These issues were exacerbated by staffing turnover and made it difficult to reliably bring new programs online. Smart Data was brought in as a long-term partner to investigate and resolve the technical gaps, while enabling internal teams to focus on ongoing operations.
Project Challenge
Key challenges included:
Lack of documentation due to team turnover
Lost knowledge of onboarding processes for new clients
Persistent data quality issues across multiple systems
No existing infrastructure for automated data monitoring or governance
Multiple technologies across systems, making root cause analysis complex
Urgent need to onboard four new programs with minimal disruption
Project Approach
Smart Data used a flexible Agile methodology adapted to the client’s priorities. Each initiative followed a structured process from discovery through execution, with regular reporting and budget tracking. Key efforts included:
Data Quality Resolution: Investigated and resolved issues across platforms, working with both internal teams and downstream customers to ensure high-impact fixes.
Technical Documentation: Built tools and diagrams to visualize decision trees and platform logic, making it easier for both technical and business teams to understand.
New Program Migrations: Developed a documented, repeatable process and successfully migrated four customer programs.
Governance Readiness: Designed a proactive monitoring plan using Datadog and checkpoints inside SSIS and Mulesoft pipelines to automatically validate data integrity and allow user-defined actions.
Smart Data supported each effort through combined onshore and offshore team collaboration, detailed estimates, and iterative delivery using backlog prioritization and sprint-based execution.
Project Results
The outcomes of this enterprise data quality transformation included:
Key Technologies
This solution utilized Java and Angular for application enhancements, SQL and MongoDB for data handling, SSIS and Mulesoft for pipeline integrations, and Datadog and OnBase for observability and enterprise document management.
