In today’s modern world, managing data on a single platform is preferred due to its various advantages such as work efficiency, data security, reliability, cost-effectiveness, etc. It's kind of a challenging task to do it in correct way and to overcome this, engineers created some of the platforms based on ETL architecture which gives an overall single-handed environment with customer support, the addition of functionality, timed updates, and many more.

1. What is ETL?

ETL stands for Extract, Transform and Load.

1.1 Extract

It is the process of extraction of data from external sources such as a database or a warehouse to initiate the workflow.

1.2 Transform

For data integrity to be maintained, different data transformation techniques are used to perform data cleaning, sorting, creating required columns, and removing redundant data to optimise the result which will be given in the future.

1.3 Load‍

In this step, data is transferred to its final destination making it accessible for further processing.

2. Benefits of ETL and why do we need it?

ETL collects and redefines data and delivers them to a data warehouse. The process of ETL plays a crucial role in data integration strategies. It is the process of moving raw data from one or more sources into a destination warehouse. It allows businesses to gather data from multiple sources and consolidate it into a centralised location. This is essential in preparing the data for analysis to have a seamless business intelligence system in place. These tools are applications or platforms that help businesses move data from one or many different data sources to a destination. These tools aid in making data both comprehensible and accessible in the desired location, namely a data warehouse.

Selecting a good ETL tool is essential to a Data Engineer. An ETL tool automates most of a company's workflows without human intervention. It also provides a highly available service. Henceforth, choosing a perfect ETL tool is vital in future use cases.

ETL Cycle is as follows:

1. Cycle initiation
2. Build reference data
3. Extract
4. Validate
5. Transform
6. Stage
7. Audit reports
8. Publish
9. Archive

3. Factors to choose a right ETL tool

3.1 Usability

‍It must have a user-friendly interface such that a less technical person could also use it with the training of a few days. Moreover, users should be able to navigate between different features/sections within a very few clicks which makes it less complicated and more time-efficient. Drag-drop functionality is the most preferred and widely used in such kinds of applications.

3.2 Costing

This plays an important role as this will count in the company’s budget. There are various methods through which tools are being offered i.e. some have different tools depending on the requirements and some have only one tool and give limited access according to scalability.‍

3.3 Data Quality

‍Make sure the tool must have the support of maintaining the quality of data such as data transformation, data cleaning, etc. It would be a tedious task if one has to carry the whole data and transfer it to another platform for similar processes and bring it back or import a huge amount of data from another source.

3.4 Performance

‍The execution time of the task affects the user’s ability to perform against the work assigned on a daily basis. If the number of records is more, the tool must work optimally and should give the results in a limited time.‍

3.5 Compatibility

It should support various operating systems (in the case of desktop applications) and data sources from which data could be ingested in an easier way through APIs or connectors rather than creating pipelines through programming which is more error-prone and time-consuming. There should not be much work to be done to configure.

3.6 Support & Maintenance

‍The company should be actively participating in the support and maintenance as well if the clients are facing some issues during their work or there is a blocker. It is the responsibility of the provider to remove the blocker as soon as possible to avoid any discrepancy and moreover they must include some of the features that can be requested by the users in the future which are not present at the current time.

3.7 Batch Processing

‍In this sector, sometimes it becomes very difficult to work on complete data (due to its size) at once as it increases the time taken for accomplishing the given task. Furthermore, some tools are not optimized for handling such a huge amount of data and fail to do the required job. In this case, batch processing is preferred which keeps the record of the data/batch which is being processed, and in the next step a lesser amount of time will be taken to process the remaining data.

4. Conclusion

These are some of the ways which can be kept in mind while choosing the ETL tool. It all depends on the functionality which is being provided by the different vendors and their After-Sales services. Although to further reduce the cost, ELT tools are also present in the market which gives some more added advantages to the existing ETL tools.