If you're here, you probably have already heard about the ETL process - if not, we explain what ETL is here - and you probably know that it's essential so that companies can have control over their data, make better decisions and optimize their business intelligence strategies. If you're thinking about implementing an ETL process in your company, here are the best tools to do so.
What capabilities should an ETL tool have?
Before deciding on one option or another, it is important to consider the requirements that an optimal ETL tool must meet. According to Gartner, one of the world's leading technology research and consulting companies, an ETL tool should have the following capabilities:
- Connectivity and adaptation: An ETL tool must have the ability to connect to multiple data structures such as: relational and non-relational databases, ERP, CRM or SCM applications; files in different formats, web pages, email, office tools or content repositories.
- Data delivery: The tool must also have the ability to provide data to other applications, processes or databases in various formats.
- Data transformation: An ideal ETL tool must be capable of performing data transformations. These can be basic transformations (simple calculations or type conversions), intermediate transformations (aggregations, sums, etc.) or complex transformations such as text analysis.
- Metadata and data modeling: Our tool must be able to retrieve the original data models, create and maintain models, synchronize changes in the metadata and have an open metadata repository.
- Design and development environment: Similarly, it must have the skills to graphically represent the objects in the repository, test and debugging support, manage workflows, etc.
- Data management: A suitable tool must be able to validate data quality, create profiles, have data mining capabilities, etc.
- Adaptation to other platforms: It is essential that the tool adapts to other operating systems and hardware platforms of the organization.
- Administrative operations: The tool must be able to monitor data integrations, handle errors, execute security controls, etc.
- Architecture and integration: An ETL must guarantee the interoperability between the different elements that make up the data integration tool.
- SOA (Service Oriented Architecture).
Types of ETL tools
Once we have clear the technical capabilities that an ETL tool must have, it is necessary to know the different categories of tools that exist, since according to the characteristics of our company and the amount of data we want to load and transform, as well as the use that we are going to give them, we should choose one tool or another.
- ETL Enterprise: These tools have many functionalities and can connect to a wide range of data sources. However, their cost is higher than the others, so they are usually chosen by very large companies.
- ETL Open Source: Free and open source ETL tools. These tools have a general approach and therefore, often require difficult customization processes so that they can be adapted to the companies' needs. The customization requires experts, usually external to the company, which ends up meaning that these types of tools, despite being free, have an additional cost.
- Customized ETL: Companies can develop their own customized ETL tools. Although they usually meet the company's specific requirements, their development is very expensive, requires experts and involves a great deal of prior effort.
- ETL Cloud: Google, Microsoft and Amazon have their own ETL services integrated into the cloud. This type of services provide more flexibility than other types of tools.
What we need to consider
Once we have a clear idea of the types of ETL tools that we can find in the market, it is essential to know what we should base our choice of tool on. It is important to emphasize that there are no better or worse tools, but simply that some will be more suitable than others according to the particularities, needs and amount of data of the company.
When choosing an ETL tool we must consider, at least, these aspects:
- The price: Not only the cost of acquisition, but also the added costs such as consulting, support, training, etc. Depending on the tool we choose, the added costs will be higher or lower. As we have already mentioned, choosing an Open Source tool usually implies added costs.
- Usability: It is elementary to keep in mind that some tools have a more complex use than others, and that each one requires a different level of technical knowledge. For example, tools with a friendly graphic interface are usually easier to use for non-experts.
- Compatibility: It is essential to ensure that the tool is compatible with the company's other operating systems and platforms.
- Speed: The speed of an ETL tool depends on its calculation capacity and on the amount of data we need to extract and load.
- Data quality: A key aspect of the ETL process is that it is a guarantee of the quality of our data. Therefore, when choosing the tool we must be sure that it will validate, cleanse, and consolidate the data.
- Management and control: It is also relevant to choose a tool that has control systems to identify and solve problems or errors that may arise.
Market-leading tools: Gartner's Magic Quadrant
In addition to the list of capabilities that ETL tools should have, Gartner also publishes a report every year called 'Gartner's Magic Quadrant' which lists the best tools for data integration in different categories: Challengers, Leaders, Niche players and Visionaries. The companies that enter the ranking are distributed in a square graph, referenced by each of these terms in one of the corners.
The last Gartner report from August 2020 placed Informatica, IBM, Talend, SAP, Oracle, SAS, Denodo, Microsoft Azure, Qlik and TIBCO Software as the top 10 ETL tool vendors. You can view the complete list below:
Benefits of acquiring the right ETL tool
In this blog we have talked about the benefits of implementing an ETL process before. However, let's review the competitive advantages of choosing the right ETL tool:
- Data-driven decisions: One of the most important benefits of the ETL process is that it allows organizations to make better business decisions based on quality data. Data-driven decisions prevent errors and ensure the development of more efficient business strategies in less time.
- Data quality: In an ETL process the data is purified and cleaned. Redundant, unnecessary or error-prone data is eliminated; whereas useful and reliable data is validated.
- Data integration: The ETL process allows data to be available in multiple formats and from multiple sources. In other words, this process allows all the data of our company to be integrated and helps to have a global and more accurate vision of the activity and situation of the business.
- Automation: ETL tools have the ability to automate certain processes, thus reducing unnecessary tasks and time spent by people in charge of data management.
- Big Data: The process also allows companies to process, work and manage large amounts of data.
- Legibility: The ETL process transforms data -even the less readable ones- into understandable, useful and ready to be analyzed information in data analysis applications such as Power BI. Bismart, as a Microsoft Power BI partner, uses this tool to develop visually attractive and useful reports and charts.