About Pipelines
A data pipeline automates the movement, transformation, and management of data from various sources to a destination, such as a data warehouse or database. Data pipelines are essential for modern enterprises, ensuring efficient and reliable data management throughout its lifecycle.
Key Components of Data Pipelines
- Data Sources: The origins of your data, such as databases, APIs, and streaming services.
- Data Intake: The process of collecting data from sources.
- Data Transformation: Converting data into a usable format.
- Data Storage: Saving data in warehouses or databases.
- Processing: Performing operations on data to generate insights.
- Data Movement: Transferring data between systems.
- Orchestration and Automation: Coordinating tasks to ensure smooth operation.
- Monitoring and Error Handling: Tracking performance and managing issues.
- Data Quality and Governance: Ensuring data accuracy and compliance.
- Data Consumption: Using data for business intelligence, analytics, and machine learning.
These components enable businesses to effectively acquire, process, and utilize their data assets for decision-making and competitive advantage.
ADOC Pipeline
ADOC Pipeline feature augment multi-platform pipelines built on modern data stack orchestration tools and data platforms with data-aware performance, reliability, and timeliness observability. Following components of ADOC pipeline will aid your understanding.
Pipeline: The pipeline is the root entity in ADOC Pipelines. Data pipeline executions, metadata, and metrics are all included for research and monitoring.
Pipeline Run: With each execution, or Pipeline Run, ADOC Pipelines keeps track of a pipeline's versioning, metadata, and metrics.
Pipeline View: The Pipeline List View lists all ADOC pipelines and offers analytics. Pipeline list view opens when you click the Pipeline symbol in the left navigation bar.