Comprehensive Data Analytics Platform for Pharmaceutical Market Insights

The client faces limitations in product development capacity, lacking the agility to meet evolving market demands. They have insufficient in-house expertise to adopt latest development practices, causing delays in releasing new analytics products. Additionally, they lack a scalable platform capable of replatforming their legacy systems, hindering efficient data processing and reporting from multisource data assets while maintaining patient privacy and compliance standards.

A large-scale pharmaceutical analytics company specializing in processing vast datasets of patient records and patents to support healthcare research and market analysis.

• Redesign and develop a scalable, high-performance BI platform capable of handling multisource, multiformat data for pharmaceutical market analysis.
• Implement an automated data processing system that significantly reduces data load and query times, aiming for at least a 35x performance improvement.
• Create modular data management and visualization applications that support standalone operations or integrated usage, improving accessibility for technical and non-technical users.
• Enable rapid product development cycles with tools for data ingestion, transformation, and reporting, reducing time-to-market for new features and products.
• Incorporate advanced reporting, including market share, launch dynamics, demographic insights, milestones, and extended metrics with map integration.
• Establish secure data access management and data sharing controls with role-based permissions for different user groups.
• Ensure platform scalability, efficiency, and compliance with healthcare privacy standards through cloud migration and distributed processing capabilities.

• A centralized Business Intelligence (BI) platform with dynamic report generation and customizable dashboards.
• Automated ingestion, cleaning, transformation, and processing of multisource data (CSV, XLS, TXT, archived files, etc.).
• Enhanced report types including share of market, launch dashboards, demographic analytics, and milestone indicators.
• Mapping and geographical visualization support for reports by countries and regions.
• Data sharing modules with export in presentation-ready formats and integration with cloud storages.
• User-friendly web interfaces for non-technical users to manage ETL processes, access data, and generate reports.
• Role-based data access control and data visibility restrictions.
• Forecasting and predictive analytics features based on historical data patterns.
• Integration with external data sources such as cloud storage, enterprise databases, and survey tools.
• Scalable architecture supporting horizontal and vertical growth, with enhanced processing speeds and reduced resource consumption.

• Enterprise CRM and marketing systems via APIs (e.g., Salesforce) for data sharing
• Cloud storage services for data archiving and delivery
• Existing databases such as Oracle and Microsoft SQL Server
• Survey platforms for data collection and analysis
• Data processing engines supporting distributed storage and processing

• Query performance improved by at least 35x over legacy systems
• Data processing to be completed within minutes, supporting real-time or near-real-time analytics
• Platform to support at least a 10x increase in data volume without performance degradation
• Role-based permission models for data security and visibility controls
• High availability and fault tolerance in cloud environment
• Compliance with healthcare data privacy standards (e.g., HIPAA) and secure data handling practices

The new analytics platform is expected to dramatically improve data processing speeds, reducing query times by 35x, and facilitate faster product releases. It will empower non-technical users to manage data workflows easily, lead to better market insights through advanced reporting features, and support scalable growth. Ultimately, this will enable the client to maintain a competitive edge in pharmaceutical analytics, increase operational efficiency, reduce infrastructure costs, and enhance decision-making capabilities.