Data Pipeline
A series of steps or processes involved in collecting, transforming, storing, and analyzing data
Overview
A data pipeline is a sequence of connected processes that move and transform data from source systems to destinations where it's needed. In healthcare, pipelines ensure reliable data flow from medical devices, EHRs, and other sources to analytics systems and AI models.
Core Functions
Data pipelines perform three main functions:
- Collection → gathering data from various sources
- Processing → transforming data into useful formats
- Delivery → moving data to where it's needed
Data Sources
- Electronic Health Records (EHR)
- Medical devices and sensors
- Laboratory systems
- Imaging equipment
- Patient portals
Healthcare Applications
Clinical Data Flow
Patient data moves through several stages:
- Raw data capture
- Vital signs
- Lab results
- Clinical notes
- Processing
- Format standardization
- Privacy protection
- Quality validation
- Distribution
- Analytics systems
- Research databases
- Reporting tools
Real-time Processing
Time-sensitive data requires:
- Immediate capture from devices
- Rapid validation checks
- Quick routing to critical systems
- Continuous monitoring
- Error detection
Quality Controls
Validation Steps
Each pipeline stage includes:
- Data quality checks
- Format verification
- Completeness assessment
- Privacy compliance
- Error logging
Monitoring
Systems track: → Pipeline performance → Data flow rates → Error rates → Processing times → System health