Coforge Improved Data Stewardship for A Leading Pharmaceutical Company
Overview.
Our client, a prominent American Life Science Company with a focus on CNS (Central Nervous System), is part of a larger conglomerate. With a wide global presence, the client required a robust IT ecosystem to smoothly manage its comprehensive data. The client was seeking a partner with data expertise & a strong domain understanding. Coforge capitalized on a holistic approach to tackle the data paradigm of the pharmaceutical company.
The client was facing multiple data issues, including:
Setting up data governance and quality control processes to increase ROI (Return on Investment) for its cloud-based data lake.
Preparing a data management platform (to address future requirements) at a lower cost of ownership (TCO).
To address the challenge, the client was seeking a skilled team that could meet compliance and regulatory requirements.
Solution
Coforge formulated an all-encompassing solution to resolve client’s issues. Below are some of the key points:
Data Assessment & Evaluation
Coforge examined the entire data ecosystem, including data quality/storage/consumption to gain a complete understanding. A master data management (MDM) health check for Data Lake hosted on the Azure Cloud platform. For a deep analysis, we identified data issues or challenges.
Data Management
Appointed domain-specific data stewards to perform the following business-specific tasks:
Data Exclusions – Removed irrelevant and low-quality data from the data ecosystem. This process required identifying and defining criteria for the exclusion of specific data elements.
Data Standardization – Established consistent formats to ensure that data is represented in a standardized way.
Data Enrichment – Enhanced data by adding more valuable and actionable attributes for businesses.
Data Curation – Cleaned, monitored, and maintained data to keep it up-to-date and accurate.
Set up IDE system
Coforge evaluated the current state of the customer master data management (MDM) system and improved on match and merge rules. To handle and resolve exceptions in the master data, we deployed IDQ (Identity Data Quality) and IDE (Identity Data Exception).
Data Audit
Set up audit balance control across commercial data environment comprising Data Lake, MDM, CRM, and Sales Incentive system. It helped the client to get early warning and data notification for data mismatch.
The Impact
Established well-defined data quality and data governance process. It helped the client certify commercial data environment on a monthly basis.
Improved data stewardship and business confidence in MDM data.
Early warning and proactive notification for data issues.
