Title: ELT
Author: Kriko
Published: Jun 15, 2023
Last modified: Jul 7, 2026

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# ELT

ELT is a data integration method used to collect, centralise and analyse large datasets
in a structured and scalable manner. The term stands for Extract, Load and Transform.

In an ELT process, data is extracted from multiple source systems and loaded directly
into a central data warehouse, data lake or cloud-based storage environment. The
transformation stage is then performed within the target system.

ELT is commonly used in big data, cloud analytics and data warehousing projects.
Consolidating diverse and complex datasets within a single environment makes them
easier to manage, process and analyse. It also allows organisations to scale their
analytical workloads more efficiently.

By simplifying data integration and taking advantage of the processing power of 
modern cloud platforms, ELT can reduce the time and resources required to prepare
data for analysis. For this reason, it has become a widely adopted approach among
organisations that manage large volumes of structured, semi-structured or unstructured
data.

The ELT process consists of three main stages:

**Extract:** Data is retrieved from source systems such as databases, applications,
files, APIs and external platforms.

**Load:** The extracted data is transferred to a central storage or analytical environment
in its original or near-original form.

**Transform:** The data is cleaned, standardised, combined and converted within 
the target system according to analytical and business requirements.

Loading data before transformation enables faster ingestion and provides greater
flexibility for data analysis. Since the original data remains available in the 
target environment, organisations can apply different transformation rules to the
same dataset without having to extract it again.

ELT offers several benefits to businesses, particularly when working with large 
and complex datasets. Centralising data in a single environment improves accessibility
and allows authorised users to retrieve relevant information more quickly.

Once the necessary transformations have been completed, data becomes ready for reporting,
analysis and decision-making. Faster access to data can also support cost efficiency
by reducing the need for multiple tools, duplicated processes and repeated data 
transfers between different systems.

By minimising unnecessary data movement and using the scalable processing capabilities
of the target platform, ELT helps organisations access and analyse data more efficiently,
quickly and cost-effectively.

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