Today, in organisations with non-optimised ETL tools, 50% of the data obtained arrives much later for analytics software. This situation means that, on average, 75% of companies lose business opportunities by not being able to count on the information quickly and in a timely manner. That’s why an ETL solution is one of the first things to have when you want to develop your business.
Improving ETL processes and their associated tools is a necessity for organisations that wish to achieve greater growth, both commercial and productive.
There’s no doubt that ETL tools are the main instruments that allow us to build a data warehouse or data mart. However, it is not always easy to know how to choose the right solution that best suits our objectives, that’s why business’ owners usually need somebody to assist in this case. There are not so many companies which work with ETL solutions today, however several IT companies, such as Visual Flow, provide professional services. This post will explain the different categories of ETL tools and make a comparison of the main tools in the market.
What are features of working with ETL tools?
ETL is the process that allows you to extract data from heterogeneous sources and with different formats in one place. In addition, the data is validated, cleaned and the necessary transformations are applied so that they can be analysed easily; finally, the data is loaded into a database, data warehouse or data mart, where they are ready to be exploited.
Moreover, this ETL process can become very complex, also taking into account the large size of the data to extract, transform and load. Therefore, ETL tools play a fundamental role since they are the basis for any data analysis and business intelligence strategy.
What are the main stages of the ETL process?
When it comes to non-complex ETL processes, the three stages are usually concatenated with each other. As a rule there are stages such as extraction stage, transformation stage,load stage.
However, as a process increases in complexity, each phase can be developed separately and using specific ETL tools. Specifically, in the three stages the following happens:
The first one is the extraction stage. In this first phase you get the ‘primary material’ with which you will work on the following ones. It is about extracting raw or pure data from sources such as:
- social networks,
- CRM software,
- telephone records,
- invoices issued.
Because they are of a varied nature, these data are subjected to a homogenisation process before being sent to the transformation phase.
After the data is obtained and homogenised, a process is applied to them to obtain value and usefulness from them. That is, at this stage the homogenised data is converted into practical and useful information for the company.
Finally, the outgoing information of the transformation stage is uploaded to a data warehouse. Once it is on this site, it can be consulted, shared or analysed by the company’s staff. That is, the loading phase is the one that makes the data available to non-technical personnel.
All you need to know about this innovative solution
There are different ETL tools on the market, each with its own specific characteristics. However, when choosing the right tool for our company or project, services are faced with four different main categories:
- ETL Enterprise tools. These are proprietary products, with many functionalities included and support for connection with a large number of sources and are usually chosen by large companies since the acquisition cost is high.
- Open source ETL tools. These are free-code and free-use tools, which allows greater accessibility for small companies. Being products with a general approach, customisation is often necessary to adapt to specific objectives, which requires specialised consulting.
- Customised ETL tools. These are tools developed to measure and specifically for a specific company or project. They require a great initial development effort, but the result is better suited to the requirements.
- ETL Cloud Tools. The cloud can provide us with all its advantages such as high flexibility and pay-per-use when choosing ETL tools that are offered as a service.
How to choose the right ETL tools?
A recent study indicates that businesses with optimised analytics processes can make decisions five times faster than the competition. Having, or not, the data management tools that best suit the organisation can make the difference between its success or failure. In this sense, choosing the best ETL tools brings the following benefits:
- It increases the ability to make accurate and timely decisions and filter all the data obtained to have only those with value and consistency.
- It allows you to obtain data of all kinds and from any source and provides automated support to the personnel in charge of data management.
- It offers agility when processing even huge amounts of data and turns unreadable data into readable, accessible and practical information.
As we have seen, all categories of ETL tools have their advantages and disadvantages. Therefore, it is important to take into account our objectives and needs, as well as the costs and resources we have at our disposal to choose whether to acquire a commercial solution, adapt an open source tool, or develop our own tool.
How to choose ETL tools for your team?
Next, we are going to discuss the main features according to which it is possible to make a comparison of ETL tools. The first one is cost, which is not only limited to the cost of acquisition, but also includes support, training and consulting costs. It is important to take into account the total of these costs to decide between a proprietary or free code tool.
The risk that the project will not succeed, which includes not meeting the budget, the schedule or the requirements or expectations of customers. Ease of use is another case, which is substantially improved if the tool has a friendly graphical interface, which can also reduce learning time.
Support and customer service. In this sense, it must be taken into account if it is offered in several languages and countries. Pay attention to the speed, which depends to a large extent on the amount of data to be transferred through the network and the computing capacity required for the transformations.
Connectivity with all types of systems is another point to check, which can allow us to extract data from all types of legacy applications, be it databases in Excel, mainframes, flat files, XML, etc.
