---
title: Data Pipelines Overview
description: Learn about the essential phases of data pipelines.
image: 'https://assets.bytebytego.com/diagrams/0157-data-pipeline-overview.png'
createdAt: '2024-03-14'
draft: false
categories:
  - ai-machine-learning
tags:
  - data-pipelines
  - data-processing
---

![](https://assets.bytebytego.com/diagrams/0157-data-pipeline-overview.png)

Data pipelines are a fundamental component of managing and processing data efficiently within modern systems. These pipelines typically encompass 5 predominant phases: Collect, Ingest, Store, Compute, and Consume.

## Collect:

Data is acquired from data stores, data streams, and applications, sourced remotely from devices, applications, or business systems.

## Ingest:

During the ingestion process, data is loaded into systems and organized within event queues.

## 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.

## Compute:

Data undergoes aggregation, cleansing, and manipulation to conform to company standards, including tasks such as format conversion, data compression, and partitioning. This phase employs both batch and stream processing techniques.

## Consume:

Processed data is made available for consumption through analytics and visualization tools, operational 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 the overall success of data-driven operations within an organization.