ETL Pipeline
The ETL pipeline, commonly referred to in Turkish as a data processing pipeline, is defined as the process of transforming data obtained from various sources into a usable format. The processed and meaningfully transformed data is then loaded into a data warehouse for analysis and storage. The system that automates this entire process is called a pipeline. The term ETL stands for Extract, Transform, and Load. You can find the details of all these stages, which collectively answer the question what is an ETL pipeline, in the table below.
Stages of the ETL Process
- Extract: Throughout this stage, raw data is collected from various sources such as CRM systems, ERP software, SQL databases, APIs, or websites. At this stage, it is determined where the data will be sourced from, how frequently it will be retrieved, and how data integrity will be maintained. For example, in an e-commerce platform, user order data can be regularly extracted from payment systems and web analytics tools.
- Transform: Following the data extraction phase, the data must be prepared to align with business processes. In this stage, data is cleaned, incomplete or erroneous records are corrected, different formats are standardized, and data from multiple sources is consolidated. For instance, sales data from different countries can be converted into a single currency standard, or date formats can be harmonized.
- Load: The final stage, known as the load phase, involves transferring the processed and cleansed data into a data warehouse, data lake, or analytical systems. At this stage, the data becomes ready for use by reporting and analytics tools. For example, sales, customer, and traffic data can be loaded into a data warehouse and analyzed through dashboards.
