A data pipeline is a system that organizes the flow of data across different stages.
“A data pipeline is a system that organizes the flow of data across different stages. Taking raw data from various sources, it is then transformed, and finally deposited it into a data store, such as a data lake or data warehouse.”
Data pipeline life cycle:
- Data intake: Extraction of data from multiple sources, such as databases, applications, APIs, and files. This phase involves collecting and capturing raw data.
- Data Transformation: This stage involves data quality checks, data formatting, merging multiple datasets, and applying business rules or algorithms.
- Data Integration: Integration of data sources, from various systems and making it available for analysis.
After transformation and integration, the processed data is loaded into a system or data warehouse, where it can be accessed for reporting, analysis, and visualization. This ensures that the data is readily available for business intelligence.
Data pipelines serve as the lifeline of data-driven organizations, enabling the smooth and efficient movement of data from diverse sources to its destination.