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What is ELT?
ELT stands for Extract, Load, and Transform. It is a data integration process for transferring raw data from a source server to a data system (such as a data warehouse or data lake) on a target server and then fitting the data for downstream uses.
The extract and load procedure can be isolated from the transformation phase. Isolating the load phase from the transformation process deletes an inherent dependency between these phases. It can include the data necessary for the transformations, the extract and load process can include an element of data that can be essential in the future. The load process can take the entire source and load it into the warehouses.
Advantages of ELT
There are various advantages of ELT which are as follows
Real-time, flexible data analysis. Users have the adaptability to analyze the whole data set, such as real-time information, in various movement, without having to wait for it to extract, transform and load information.
Lower cost and lower maintenance ELT benefits from a powerful ecosystem of cloud-based platforms which provide much lower costs and several plan options to store and process data. The ELT procedure usually needed low maintenance given that all information is continually available and the transformation procedure is usually automated and cloud-based.
Efficient ELT can take advantage of the computing power of existing hardware to perform transformations.
Flexible resulting data set When it uses ELT, it can move the entire data set to the target. This can be useful if it doesn't want to transform the data before it can move it, or it wants flexibility in the schema for the target data.
The data is nearly simple yet massive, including log documents and sensor data. In this case, the transformations that take place in the target might be relatively simple, and the benefit comes from the ability of the target datastore to load massive volumes of data quickly.
Simplifying management − ELT divides the loading and transformation services, minimizing the interdependencies among these phase, lowering risk, and integrate project administration.
Leveraging the latest technologies − ELT solutions exploit the power of new technologies to shift development, security, and compliance across the enterprise.
Scalability − The scalability of cloud infrastructure and hosted services like integration platform-as-a-service (iPaaS) and software-as-a-service (SaaS) give organizations the ability to expend resources on the fly. They insert the compute time and storage space essential for even a massive data transformation service.
Future-proofed data sets − ELT implementations can be used precisely for data warehousing systems, but ELT is used in the data lake method in which data is collected from an area of sources. Therefore, it is mixed with the separation of the transformation process, creating it simpler to make eventual modifies to the warehouse architecture.
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