What are ETL tools?
Everything around us is a representation of data. Similarly, everything in the computer world is also a representation of data as well. It will be nearly impossible for organizations to accurately recognize themselves without data. Organizations need to access data assets just like how they have to access their physical assets.
ETL stands for Extract Transform and Load. Therefore, the ETL tools in the topic will extract the data from the source transform them in the transit and load them into the necessary form. These movements of data can be scheduled to happen on a periodic basis or made to happen at a certain trigger.
The type of projects in which these ETL tools are used varies greatly as this software are very flexible. Some of the areas where the ETL tools are used are listed below:
- Rolling up transactional data for business people to work with. – Data Mart and Data Warehouses.
- Migrating application data from old systems to new ones.
- Integrating data from recent corporate data and acquisitions.
- Integrating data from external suppliers and partners.
Imagine having to hand code all the data migrations form all the source and destinations the organization owns. A large body of logic will be designed in the data movement process and it will become the basis for running the business. Therefore make a good analysis of the requirement of the organization before purchasing an ETL tool.
Things need to be considered before choosing what ETL to use:
- Data Connectivity: ETL tools should be able to communicate with any source of data. Even if the organizations do not have a certain type of computer now, it might suddenly have lots of them when it another organization as it grows.
- Performance: Moving and changing data will require lots of processing power. So the ETL data software should be in an environment that can scale with future data demands.
- Transformation Flexibility: Matching, merging and changing data is critical. ETL tools should provide options to do these changes with simple drag and drop movement.
- Data Quality: The data is as a resource is not clean, and so a developer needs support for data profiling and data quality check, including the ability to validate the address. The data should be consistent and clean after the quality check to ensure further reliability.
- Flexible data acquisition options: Once the ETL environment is set up, the developer should have the ability of data acquisition based on the time interval or trigger.
- Reliable Vendor to ETL: Finally, the vendor of the ETL should be reliable to make sure that the organization doesn’t run into trouble because the Vendor suddenly removed support for the specific ETL tool.
Why ETL is needed?
In the real world, we face many data problems. Some of the common problems are that data is located in many geographical locations, it is in a different format from other data, different customers have data in different kinds of resources. Along with these challenges data increases with time. Data does not necessarily be structured into tables. Sometimes, even if the data is structured, it might be in poor design after all.
A good example for a different kind of data is when one customer has data in the flat file, one in XML and one in excel file. Another aspect of this data is that the volume keeps increasing.
This data can be structured, semi-structured or it can also be unstructured. To face all these problems, we need someone to manage all these data in an efficient and useful way.
ETL is one stop solution for facing and solving the above solution.
Below we explain how ETL tools face these problems one after another. The process is fairly straight forward and they are listed one below another:
Extraction is the process of getting all the data from the files. Also, businesses in production might be dependant on the data, so it needs to be extracted without disturbing the production applications. It is independent of the type of file or the source of the file. This step just acquires all the data and brings into the picture for further work. This data is stored in XML, Excel, and databases as well.
Transformation is the process of changing the definition of the data or value in data of the source so that the total extracted data work with each other irrespective of the source or file format. So we can say that transformation will include Clean, Split, Enrich, Join.
Loading is the process of saving the transformed data for later use with minimum hardware usage.
These three tasks are difficult in their own right that they have their own subdivision as you have seen. Usually these three steps carried out many times to get the data that is reliable enough to make business decisions.
Now that we have Understood the essentials of ETL tools, lets see what are the best ETL tools in the market now
Clover is used by companies of all types to tackle the most complex data challenges out there. Clover is a great product that is backed up by great customer support as well. With Clover, the user can Design, operate and automate data transformation jobs of any scale and any complexity. It is also easy to integrate them in a new operational environment. This tool lets the uses to arrive at a finished solution faster than manual coding or other approaches. The Clover team also delivers custom solutions both remote and onsite.
Traditionally we have relied on a shared database for data exchange. But here the data is combined together and stored in advanced. Clover ETL solves difficult data transformations using this technique. In Clover ETL, the users are able to replace the target data storage with data service API for applications to use the data quickly and rapidly. It is a good combination of UI tools and full coding customization for performing ETL tasks and jobs.
Jedox introduces data-driven modelling. When data is uploaded in excel file, Jedox creates a multidimensional data for the user that is based on the file. It has intuitive drag and drop modelling for editing the data format, in the table like interface. The user can use the same interface to redesign the hierarchy within the data structure. The data is analyzed and helps the user to quickly build a planning template.
It also has multi-cell entry, this helps the user to enter data in a range of cells or cells that are scattered across the table.
Offline mode for Jedox excel adds the following awesome features:
- Hidden spreadsheet.
- Scheduled backups
- User-defined password policy.
Pentaho Data Integration (Kettle):
Kettle Extraction Transformation Transportation and Loading Tool. It is an open source business intelligence suite by Pentaho. Below is the detailed introduction to Kettl.
This has the following components:
- Carte: It is a simple web server to execute transformations and jobs symmetry execute XML that contains transformations to execute and execute transformation.
- Spoon: It is a GUI that allows the users to design transformations and Jobs that can be run with kettle tools.
- Kitchen: jobs and transformations can be described using an xml file, and can be put in kettel repository.
- Pan: A program to execute that data designed in XML by spoon or data repository. It is scheduled in batch mode to run automatically in regular interval.
- Kitchen: It executes jobs designed by kettle ETL tool or database or XML.
This ETL tool can be used when there is a higher need for migrating data between application and databases, data cleansing, integrating applications and loading data massively into databases. This can be done using GUI without having to program using code. Because of this, we can say that Kettle is meta data-oriented ETL software that is open source as well.
Talend is easy to use GUI based application. It has built-in error handling. Reduce expenses and Better data management. When there is an incremental load, this ETL tool manages the load very well. It gives an increase in performance even in such complex situations.
Talend is an open source ETL tool. It is offered by Talend and it is called “Talend open studio“.
It offers various integration and data management solutions. Talend is a code generator that converts all the underlying program into Java in the backend. It allows the user to interact with a drag and drop style UI to recreate the necessary use case and let the Talend Open Studio convert it to java. The backend code is not editable and therefore any change in the use case must be implemented in the drag and drop UI only.
With Talend, the user can manage all the ETL tasks easily. Easily manage the data with the source and destination with simple drag and drop. It is a very sophisticated tool and therefore, different kind of database can be made to work together as it has tools for that built in it. It avails strong connectivity and smooth flow of extraction and transformation of data.
The above are some of the best Open Source ETL tools. There are many out there that can be included in this post but we have chosen only the best ones. Each one is good at what it does and so we cannot really choose one as the best and other as otherwise. Please go through the post carefully to get the best opensource ETL tools of your need.
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