What is ETL (Extract, Transform, Load)?
Turkish: ETL
ETL extracts data from multiple sources, transforms it, and loads it into a data warehouse or reporting system on a schedule.
What is ETL?
ETL (Extract, Transform, Load) is the process of collecting data from different sources, cleaning and transforming it, and loading it into a data warehouse, reporting database, or analytics environment. The goal is to make scattered data reliable and queryable.
What Are the Stages?
- Extract: Data is collected from ERP, CRM, e-commerce systems, files, APIs, or databases
- Transform: Formats are converted, data is cleaned, joined, calculated, and validated
- Load: Prepared data is written to the target table, warehouse, or dashboard backend
For a daily sales report, orders may come from an e-commerce platform, costs from ERP, and ad spend from advertising platforms. ETL brings those sources together by date, product, and campaign.
ETL vs ELT
In ETL, data is transformed before it is loaded into the target. In ELT, raw data is loaded first and transformed inside the destination platform. ELT is common in cloud data warehouses, while ETL remains practical for smaller and more controlled reporting flows.
Business Use
ETL supports management reports, inventory analysis, customer segmentation, financial reconciliation, and operational dashboards. If a data pipeline lacks error handling, retries, data quality checks, and traceability, reports lose trust. Automation should be designed not only to move data, but also to stop bad data early.
Related Terms
Batch processing runs data in scheduled groups rather than instantly, producing reports, transfers, or transformations.
Big DataBig data is the practice of processing and analyzing datasets whose volume, speed, or variety exceeds traditional tools.
Data LakeA data lake stores raw and processed data in scalable storage for analytics, machine learning, exploration, and archiving.
Data PipelineA data pipeline collects, cleans, transforms, and moves data from sources to a target system for reporting or analytics.
Data SynchronizationData synchronization keeps records aligned across two or more systems so operations stay consistent and up to date.
Data WarehouseA data warehouse stores cleaned, structured data from multiple sources for analytics queries, KPI tracking, and business reporting.
Master Data ManagementMaster Data Management governs critical customer, product, and supplier records through a single source, quality rules, and approvals.
AutomationAutomation is the use of software or technology to perform repetitive business processes automatically, without human intervention.