In today’s world, A business needs to manage its physical assets they also need to manage the data its organization produces. This is when the ETL tools play a vital role and assist the organization in ETL Data Transfer and remain competitive in the market.

ETL stands for Extract, Transform and Load. Just as the name implies, these tools extract data from a given source this could be a properly structured database or a flat file or data from web apps, or it could be as trivial as data from sensors just in the form of 0s and 1s. The second step is transforming the data while in transit, which involves making the data readable performing complex data type conversion to performing arithmetic/logical operations, and then finally loading the data to the given destination storage.

Some common projects where ETL Data Transfer is a must are :

1. Pulling up transactional data (sale + purchase) for company heads to work with and generate visualization reports. This is commonly known as Data Warehousing.
2. Migrating data from legacy systems to new systems due to change application/platform.
3. Data integration is triggered due to corporate mergers and acquisitions.
4. ETL could also help in integrating data from third-party suppliers/vendors or partners in the Supply Chain Management Cycles.

This picture depicts how critical ETL tools are in managing data generated throughout your organization.

Which ETL Data Transfer Tool to choose :

Considering the above image, every organization must spend some on R&D to determine which ETL tool they should choose that fits best into their business. Below are some of the criteria any ETL tool must adhere to:

1. Data Connectivity: Chosen ETL tool must have the ability to connect to any data source no matter where it is coming from. This is critical!
2. Performance: dealing with a huge amount of data and transforming it definitely requires some great processing capabilities. Hence the ETL tool you choose should be able to scale up with growing data rates.
3. Rich Transformation Library: Transforming the data manually requires writing thousands of lines of code which is highly prone to errors. So in order to enable smooth data transformation, your ETL tool must extend a rich library of functions and packages which are also as easy as drag and drop facilities.
4. Data Quality Check: You can never just pick up the data from a given source and start working on transforming it. Your data is never that clean enough; hence, you are not suitable to go. You will definitely require some data cleaning support from your ETL tool.
5. Committed ETL vendor: As the above points mention all the reasons why ETL is a critical process, it is also important to choose a committed ETL vendor who knows in and out about the tool and can provide good support all throughout the project.

We at Bista Solutions evaluate the business requirements of our clients and in accordance, we offer the best suite of solutions that will cover all the pain areas of our clients and give them an AtoZ solution.

If you have any queries for ETL contact us or drop an email at sales@bistasolutions.com.