A term that is used extensively in the data world is ETL, or extract, transform, and load.
ETL is a process that moves data from a source system into a central, common destination where it can later be used for analysis. Extraction involves retrieving data from a source system, which can be in many different formats. This data is then typically loaded into a temporary staging ground where it can be transformed. Transformation seeks to structure, aggregate, and enrich the data from the staging ground, into a format that is useful for a business need. Once the data is transformed, this data is loaded into a central destination, which is often a data warehouse.
ETL Integration
A term that is used extensively in the data world is ETL, or extract, transform, and load.
ETL is a process that moves data from a source system into a central, common destination where it can later be used for analysis. Extraction involves retrieving data from a source system, which can be in many different formats. This data is then typically loaded into a temporary staging ground where it can be transformed. Transformation seeks to structure, aggregate, and enrich the data from the staging ground, into a format that is useful for a business need. Once the data is transformed, this data is loaded into a central destination, which is often a data warehouse.
A newer term, ELT (extract, load, and transform), has been gaining popularity over ETL processes as it provides more flexibility for the ultimate use of the data.
While the extraction of data from a source system remains the same, instead of transforming the data, the data is loaded raw, directly into a destination. This provides more flexibility than the traditional ETL process because it allows for the raw data to be transformed for as many business cases as are needed. Instead of being limited to the transformation process before a load, data can now be transformed while leaving the data in its immutable state.
The Untitled Approach.
ETL has long been an important process in obtaining data necessary for analysis and business intelligence. The ability to extract, transform, and load data into a common destination means that end users have the ability to ask any question from the data that would normally be constrained within an isolated system. When data is stored within a data warehouse, this opens the possibility for business intelligence, artificial intelligence, and machine learning to be utilized, providing deep insights for decision-makers to run their business.
Untitled helps businesses implement ETL processes to obtain data from all of your data sources and systems. Using tools like Fivetran and Stitch, Untitled can reduce the time and complexity of developing custom ETL/ELT processes and shift the focus to generating value from your data by preparing all of your data for each unique use case. Need custom ETL/ELT? Sometimes there are situations where tools like Fivetran and Stitch cannot natively connect to a data source that you need. In these situations, we’ll help you develop a custom ETL/ELT process.
