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Extract, transform, load (ETL) is a three-phase computing process where data is extracted from an input source, transformed (including cleaning), and loaded into an output data container. The data can be collected from one or more sources and it can also be output to one or more destinations.
Data extraction is the act or process of retrieving data out of (usually unstructured or poorly structured) data sources for further data processing or data storage (data migration). The import into the intermediate extracting system is thus usually followed by data transformation and possibly the addition of metadata prior to export to another ...
Spatial extract, transform, load (spatial ETL), also known as geospatial transformation and load (GTL), is a process for managing and manipulating geospatial data, for example map data. It is a type of extract, transform, load (ETL) process, with software tools and libraries specialised for geographical information. [1] A common use of spatial ...
Data loading, or simply loading, is a part of data processing where data is moved between two systems so that it ends up in a staging area on the target system.. With the traditional extract, transform and load (ETL) method, the load job is the last step, and the data that is loaded has already been transformed.
In the data warehouse practice of extract, transform, load (ETL), an early fact or early-arriving fact, [1] also known as late-arriving dimension or late-arriving data, [2] denotes the detection of a dimensional natural key during fact table source loading, prior to the assignment of a corresponding primary key or surrogate key in the dimension table.
The general process uses traditional methods from information extraction and extract, transform, and load (ETL), which transform the data from the sources into structured formats. So understanding how the interact and learn from each other.
Extract, transform, load (ETL) design and development is the design of some of the heavy procedures in the data warehouse and business intelligence system. Kimball et al. suggests four parts to this process, which are further divided into 34 subsystems [3]: Extracting data; Cleaning and conforming data; Delivering data for presentation
A staging area, or landing zone, is an intermediate storage area used for data processing during the extract, transform and load (ETL) process. The data staging area sits between the data source(s) and the data target(s), which are often data warehouses, data marts, or other data repositories.