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ELT
ELT (Extract, Load, Transform) is a modern data integration process that reverses the order of traditional ETL (Extract, Transform, Load) workflows.
ELT (Extract, Load, Transform) is a modern data integration process that reverses the order of traditional ETL (Extract, Transform, Load) workflows. In ELT, raw data is first extracted from various sources and loaded directly into a target data warehouse or lake without prior transformation. The transformation step occurs afterwards within the destination system, leveraging its processing power and scalability. This approach allows for greater flexibility, as analysts can transform data on-demand and iterate on transformations without re-extracting or re-loading. ELT is particularly well-suited for cloud-based data warehouses like Snowflake, BigQuery, or Redshift, which can handle large-scale data transformations efficiently. Tools like dbt have popularized ELT by providing a framework for managing and executing in-warehouse transformations using SQL.
Related terms
ETL →
ETL (Extract, Transform, Load) is a data integration process that combines data from multiple sources into a single destination, typically a data warehouse…
data pipeline →A data pipeline is a series of interconnected processes that extract data from various sources, transform it into a usable format, and load it into a…
Data transformation →Data transformation is the process of converting data from its raw, source format into a structured form suited to analysis — through operations like cleaning, joining, aggregating, and reshaping.
data build tool (dbt) →dbt is an open-source command-line tool that enables data analysts and engineers to transform data in their warehouses more effectively.
data load tool (dlt) →Data Load Tool (dlt) is an open-source Python library that automates extracting data from sources and loading it into destinations like DuckDB and MotherDuck, with automatic schema inference and incremental loading.
pipelines →Data pipelines are automated workflows that move and transform data from various sources to one or more destinations.
