ETL andELT

ETL (extract, transform, load) and ELT (extract, load, transform) are both data integration techniques that are used to transfer data from source systems to target systems. The main difference between ETL and ELT lies in the order of the data processing steps:

•    In ETL, data is first extracted from source systems, then transformed into the desired format, and finally loaded into the target system. This means that the transformation step takes place outside of the target system and can involve complex data manipulation and cleansing.

•    In ELT, data is first extracted from source systems and loaded into the target system, and then transformed within the target system. This means that the transformation step takes place within the target system, using its processing power and capabilities to transform the data.

•    The choice between ETL and ELT depends on several factors, including the complexity and size of the data being processed, the capabilities of the target system, and the processing and storage costs. ETL is more suitable for complex data transformation, while ELT is more suitable for large data volumes and systems with advanced processing capabilities.

Data Mart

A data mart is a subset of a larger data warehouse and is designed to serve the needs of a particular business unit or department. Data marts are used to provide targeted, specific information to end users, allowing them to make better, data-driven decisions.

A data mart is typically designed to store data that is relevant to a specific business area or function, such as sales, marketing, or finance. Data marts can be created using data from the larger data warehouse, or they can be created as standalone systems that are populated with data from various sources.