Table of contents
Data pipelines are a fundamental component of managing and processing data efficiently within modern systems. These efficiently within modern systems. These pipelines typically encompass 5 predominant phases: Collect, Ingest, Store, Compute, and Consume.
1.Collect:
Data is acquired from data stores, data, streams, and application, sourced remotely from devices, application, or business systems.
2.Ingest:
During the ingestion process, data is loaded into systems and organized within event queues.
3.Store:
Post ingestion, organized data is stored in data warehouses, data lakes, and data lakehouses, along with various systems like databases, ensuring post-ingestion storage.
4.Compute:
Data undergoes aggregation, cleaning, and manipulation to confirm to company standards, including tasks such as format conversion, data compression, and partitioning . This phase employs both batch and stream processing techniques.
5.Consume:
Processed data is made available for consumption through analytic and visualization tools, operation data stores, decision engines, user-facing applications, dashboards, data science, machine learning services, business intelligence, and self-service analytics.
The efficiency and effectiveness of each phase contribute to overall success of data-driven operations within in organization.