What Is ETL (Extract - Transform - Load)?
ETL is the process of
collecting data from original sources, restructuring and converting it in preparation to load it into a separate destination application or database.
How Does ETL Work?
- Extraction: data is assembled from diverse sources.
- Transformation: after data retrieval, amendments such as sorting, eliminating errors, and adding calculations are made to ensure the data conforms to the target system’s format.
- Loading: The formatted data is uploaded onto the target database or application.
What Is ETL Used For?
ETL is commonly used for data warehousing, where an organization electronically integrates all its business information across various databases into one central repository. The process makes it easy for stakeholders and other authorized personnel to access and retrieve company information for analytics purposes.
ETL is also essential for companies looking to do away with legacy systems. To keep up with technology, companies can leverage ETL applications to extract data from out of date systems, converting them into the new system’s acceptable format, and successfully loading it into the updated system.
ETL vs ELT
The main distinction is that the former restructures and converts data on an external server before loading, while the latter performs the converting and loading processes simultaneously on its server.
Additionally, the ETL process involves collecting unprocessed data and restructuring it prior to moving it into the target system. On the other hand, ELT will directly send unprocessed information into the target application.
What Are ETL Tools?
The four main types of ETL tools include:
- Enterprise Software ETL Tools
These are robust ETL tools specially designed for commercial use. They have commercial organization support and offer extensive data documentation functionalities, making them more complex.
- Open-Source ETL Tools
These are ETL tools that offer businesses access to the source code and the flexibility to design their data-sharing operations. Their functionality will vary from one application to the other.
- Cloud-Based ETL Tools
These ETL tools are hosted in the cloud, providing businesses with safe keeping for their data. They are highly efficient, flexible, and scalable, accommodating the expanding data processing demands of a business.
- Custom ETL Tools
These are ETL tools that a business develops from scratch using its preferred tech stack. Custom ETL tools offer flexibility as they are designed to suit the unique needs of an organization.
Some of the top ETL tools include:
- Pentaho Data Integration
Pentaho is an easy-to-use open-source ETL tool. It has a drag-and-drop GUI and takes a meta-data driven approach. Its enterprise version offers advanced functionalities as compared to its community counterpart.
- Hadoop
Hadoop is open-source and an ideal choice for companies with massive amounts of data to process. Its vertical and horizontal scalability options allow a higher computation power, making it the go-to ETL tool for many businesses.
- AWS Glue
AWS Glue operates on a serverless environment and offers speedier data integration. Coupled with its automation capabilities, companies can enjoy seamless ETL processes.
- Google Cloud Dataflow
Google Cloud Dataflow is ideal for large volume data processing. It is a fully-managed service, known for its high processing speeds, real-time data computation, and advanced analytic capabilities.
- IBM DataStage
IBM DataStage is ideal for large-scale enterprises, especially big data companies as it streamlines how they govern their data by offering end-to-end data integration and automation capabilities across various systems.
