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The Challenge
Leading Biotech faced significant enterprise-wide data quality challenges that needed immediate identification and resolution. They required a scalable Data Quality-as-a-Service (DQaaS) strategy to address these issues systematically. The organization needed enhanced data governance with clear policies, standards, and best practices, while aligning data quality initiatives with enterprise-wide governance frameworks to ensure sustainable improvements.
The Solution
We conducted a detailed data quality assessment, analyzing key DQ issues across the organization to identify root causes and prioritize remediation efforts. The solution included designing a comprehensive DQaaS framework that provided a structured approach for selecting flexible, scalable DQ solutions tailored to their specific needs.
We leveraged governance templates and methodologies to establish robust policies and frameworks for DQ management across all departments. The integration of DQ strategy with enterprise data governance ensured seamless implementation, including real-time quality monitoring, automated DQ score ingestion, and scalable governance workflows.
"The DQaaS framework has transformed our approach to data integrity, ensuring the reliability of our research data and accelerating our drug development pipeline."
The Results
The implementation provided a clear Data Quality Roadmap that identified root causes and priorities for addressing data quality challenges across the enterprise. A standardized, scalable approach was established for ongoing data quality improvements, ensuring consistent standards across all research and operational areas.
Stronger governance frameworks were implemented with defined standards and processes to ensure sustained data quality improvements. Most significantly, the solution achieved enterprise-wide adoption with improved governance alignment, enabling better compliance adherence and data-driven decision-making throughout the organization.
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