Life Science — Scientific Data Normalization for Regulatory Compliance
FreeThis DAG normalizes scientific data to meet regulatory compliance standards. It ensures data integrity and security through robust quality controls and access management.
Overview
The purpose of this DAG is to standardize scientific data in accordance with regulatory requirements in the life sciences sector. It begins by extracting raw data from multiple sources, including clinical trial results and laboratory test records. The ingestion pipeline incorporates data quality checks to validate the accuracy and completeness of the incoming data. Following this, Role-Based Access Control (RBAC) measures are implemented to enhance data security and ensure that only authorized p
The purpose of this DAG is to standardize scientific data in accordance with regulatory requirements in the life sciences sector. It begins by extracting raw data from multiple sources, including clinical trial results and laboratory test records. The ingestion pipeline incorporates data quality checks to validate the accuracy and completeness of the incoming data. Following this, Role-Based Access Control (RBAC) measures are implemented to enhance data security and ensure that only authorized personnel can access sensitive information. After passing quality assurance, the data undergoes a normalization process to align with industry standards, preparing it for further analysis and reporting. The normalized data is then archived in a secure storage system, accompanied by comprehensive logging to maintain traceability and compliance with regulatory mandates. Key performance indicators (KPIs) such as data quality scores, processing times, and access logs are monitored to ensure ongoing compliance and operational efficiency. The business value of this DAG lies in its ability to streamline data handling processes, reduce compliance risks, and enhance the reliability of scientific data for decision-making.
Part of the Pricing Optimization solution for the Life Science industry.
Use cases
- Ensures regulatory compliance to avoid penalties
- Enhances data integrity for better decision-making
- Reduces operational risks associated with data handling
- Improves efficiency in data processing workflows
- Facilitates easier access to reliable scientific data
Technical Specifications
Inputs
- • Clinical trial results
- • Laboratory test records
- • Research study data
- • Patient demographic information
Outputs
- • Normalized scientific data sets
- • Compliance audit logs
- • Data quality assessment reports
Processing Steps
- 1. Extract raw data from multiple sources
- 2. Perform data quality checks
- 3. Implement Role-Based Access Control
- 4. Normalize data according to standards
- 5. Archive data in secure storage
- 6. Generate compliance audit logs
Additional Information
DAG ID
WK-1387
Last Updated
2025-03-22
Downloads
24