Extract transform, and load (ETL) is utilized by companies that are data-driven to collect information from various sources , and later integrate it in order to aid in the reporting process, discovery analysis as well as decision-making and analysis.
The sources of data are varied in their formats the type, reliability and format This means that the data needs to be processed in a way that it is useful once it is collected. The data storage options could include databases, data warehouses or data lakes based on the purpose and technological strategy. If you're looking to advance your job prospects and learn more in Informatica and other related fields and fields and related fields, the Informatica Training is for you. This course can help you attain the most advanced standards in this field.
The distinct phases of ETL
In the process of extracting data, ETL identifies the data and copies it back from its source in order to transfer the information to the datastore you want. The data may be extracted from unstructured and structured sources such as emails, documents and databases, software for equipment, sensors for business and third-party sources and more.
Since the data being extracted is raw and therefore needs to be transformed and mapped so that it is prepared for storage. By transforming ETL validates or authenticates the data in order to ensure the data is secure and accessible.
ETL transforms the data to an appropriate datastore. This could be the initial loading of source data or small changes to the source data. Data can load at a speedy rate, or in scheduled batches.
Top comments (0)