Master Data Management Software Development for Pharmaceutical Customer

Client Overview
Our client is one of the largest and widely respected pharmaceutical companies in the world. The company headquarter, located in Switzerland invests billions of dollars in research and development (R&D) and globally employs approximately 100 000 people in more than 140 countries. Its core businesses are pharmaceuticals, vaccines, consumer health, generics, eye care, and animal health.

Project Overview
The client offers a wide range of healthcare products through its Pharmaceuticals, Vaccines and Diagnostics. It engages with clinical research to execute clinical development and laboratory research projects. The company's massive scope of operations in different cities meant that, large volumes of data of varied genres were being created at dispersed locations. The client could not readily establish an integrated global view of their customers and without an efficient process flow in place, clients often spent hours to collect the iterative or error data, which makes it not only time-consuming but also very difficult to manage.

The key business challenge faced was the absence of a standard project management system to view project data. What they needed most, was an integrated set of web-based data management systems and analysis tools for storing and mining information from different sources. In addition, the system also needed to facilitate data administration processes such as merge or split data file to database, archiving and deleting data/ data files; as and when needed.

Project Challenges

Data Redundancy
When collecting the data from different sources into the main system, there may exist duplicate data which is acquired from different locations. This redundant data causes quality degradation and impacts the performance of the system. It may not then portray the correct results. Data redundancy was a big challenge during data acquisition.

Inconsistent Data
The characters were inconsistent for some unique data from different data sources. The new system needed to verify the right one and discard others.

Data Changing
Sometimes the customer information of our client such as hospital combination, spin-off or employee data is changed at remote sources. These changes need to be processed properly and in time to reduce the load on the system.

Data loss
Data integrity needs to be guaranteed as data transfer from one system to another is prone to errors or loss during data acquisition and migration process.

USE solution
USE offshore team's prime focus was on understanding the client's needs thoroughly. They gathered requirements in detail before coming up with system architecture plan. Visual Studio .NET 2005 was used as the primary development tool for the project. Flexibility was kept as key concern during database design process due to the unique nature of MDM project.

Since dozens of data sources provided data annually, the processing involved multiple data types handling with different rules for critical and non-critical fields. Our teams stored raw sample data and main conclusion data while maintaining the relationship between them for the extracted attributes. Furthermore, to solve the customer data issue and ensure a single view of the customer, we created attribute tables for all data that was stored and managed in database. Their output and reports were shown to users via a .NET interface function.

Apart for that, functionalities like Province combination, City combination, Hospital and Employee integration, System administration were also considered.

Points of project:
Runtime Environment:         Window Server 2003+IIS6.0 + .Net Framework 2.0
Source Code Management:  Clear Case
Development tools:             Microsoft Visual Studio.Net 2005
Programming language:      C#, ASP.Net, AJAX
Database:                         ql Server 2005
 
Benefits

• Web-based, integrated data management system where users can incorporate or expurgate information collected from other systems into one database swiftly.
  
• Elimination of errors caused by mismatched and unreliable data from the source systems.
  
• Time Saving by not having to search information amongst the redundant data.
  
• In-depth and objective analysis pharmaceutical or medical treatment service data is always readily available.