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Most data integration tools skew towards ETL, while ELT is popular in database and data warehouse appliances. Similarly, it is possible to perform TEL (Transform, Extract, Load) where data is first transformed on a blockchain (as a way of recording changes to data, e.g., token burning) before extracting and loading into another data store.
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 concept of data warehousing dates back to the late 1980s [7] when IBM researchers Barry Devlin and Paul Murphy developed the "business data warehouse". In essence, the data warehousing concept was intended to provide an architectural model for the flow of data from operational systems to decision support environments. The concept attempted ...
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 data warehousing, a fact table consists of the measurements, metrics or facts of a business process. It is located at the center of a star schema or a snowflake schema surrounded by dimension tables. Where multiple fact tables are used, these are arranged as a fact constellation schema.
Figure 1: Simple schematic for a data warehouse. The Extract, transform, load (ETL) process extracts information from the source databases, transforms it and then loads it into the data warehouse. Figure 2: Simple schematic for a data-integration solution. A system designer constructs a mediated schema against which users can run queries.
The process of dimensional modeling builds on a 4-step design method that helps to ensure the usability of the dimensional model and the use of the data warehouse. The basics in the design build on the actual business process which the data warehouse should cover. Therefore, the first step in the model is to describe the business process which ...
If the data is being persisted in a modern database then Change Data Capture is a simple matter of permissions. Two techniques are in common use: Tracking changes using database triggers; Reading the transaction log as, or shortly after, it is written. If the data is not in a modern database, CDC becomes a programming challenge.