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Main functions of the ETL tools
There are a number of ETL tools available on the market nowadays. The ETL abbreviation stands for ‘Extract, Transform, Load’.
The basic tasks of ETL tools are:
- extract data from different systems, even on different platforms, in various forms,
- transforms them for each target system based on business needs, in the format required by the systems,
- finally, make the data generated in this way available to the target systems or load them directly.
Businesses can use data loading tools in a variety of situations, including:
- Data migration that may be required for a system implementation, system replacement, or acquisition.
- Construction, maintenance, or operation of data markets, data warehouses, data lakes, when data needs to be collected from different source systems in a raw format or along appropriate data transformations, and it has to be prepared for the business decisions.
- Ad hoc or regular processes to meet reporting needs based on the data collected.
Kamilla Kundrík
DELTA Product Manager
Kamilla has more than 15 years of sector-independent system implementation experience. She is is responsible for the business and IT development of MINDSPIRE’s DELTA tool, as well as providing support and quality assurance for the IT tasks of migration projects.
These ETL tools can be categorized by a number of criteria. One such aspect is whether the Extract – Transform – Load solution can be used as a free, open-source tool, or is available as a product to be purchased from a specialized developer. In our post, we now examine the main ETL solutions based on this criterion, but at the end of the article there is a comparison table for ETL tools in which we also compare them based on several other parameters.
Commercially available ETL tools
These data loading applications are typically made available to the general public by companies specializing on the ETL market and having extensive experience, such as Oracle, IBM, or Informatica.
These solutions have a wide range of functionality and configuration options; however, they are not primarily designed for business analysts. Accordingly, their effective application requires costly and lengthy training, and some basic or even specialized IT knowledge and perspective is also essential to use these tools.
In return, we get robust ETL solutions with performance customizable according to the individual needs and the ability to efficiently move and complexly transform large amounts of data, that can be used effectively in both heterogeneous and highly complicated environments.
Due to the expenses related to the deployment and operation of such ETL tools, their application can aim to solve large, complex, enterprise-wide problems, such as building and continuously operating data markets, data warehouses, or even data lakes to create an up-to-date business intelligence solution.
These ETL tools provide a wide range of integration options, with number of different file formats, file systems, relational and non-relational databases, various API integrations, IoT devices, big data or even cloud and hybrid cloud solutions regarding both the source and target systems.
In addition to the standard ETL capabilities, certain solutions provide a number of additional functionalities, such as data quality and data cleansing features, data security, data science, and related artificial intelligence features or master data management.
Parameterization of such data loading applications in many cases requires, not necessarily a developer, but some level of IT knowledge or IT approach. Data processes basically consist of a series of SQL functions such as join, filter (select), merge, aggregate, and so on. The input value of each element is the output value of the previous element, then it is converted according to that element until the desired target format is created. The resulting data streams even just to create a single target table can be rather long and complex chains, requiring higher attention and expertise.
The installation and utilization of these ETL tools also requires a number of preparations, for which data loading software specific administrator, or even DBA (Database Administrator) competencies are required.
Although these solutions are usually backed by complex customer service and support organizations, based on forum posts, it seems that contacting them and resolving the daily issues may not always be effortless.
Free, open-source ETL solutions
The other segment of the data loading tool market contains the free, open-source solutions. These applications are characterized by offering a much narrower set of functionalities to the users, therefore in practice their freely downloadable versions provide rather limited possibilities. However, due to the open source, these ETL tools can be customized and supplemented with development, and typically the technologies they use have proven to be reliable in the long run and do not limit the further modifications either.
In addition, common data loading tools have a large and active community, and users share their issues and experiences in forums. The development possibility also imposes conditions, as these solutions can only be suitable for companies having appropriate development competencies to fulfill the expected goals.
In addition to the freely available, but limited functionality software packages, these independent development companies are now offering paid, significantly more feature-rich solutions, which are also based on open source.
Of course, support and warranty are provided for these paid versions, as with the commercial-only data loading tools discussed in the previous chapter. Therefore open-source data loading solutions are now capable to compete with specialized solutions for the ETL market.
The parameterization capabilities of open-source data loading software are based on similar principles as the commercial tools presented in the previous chapter, namely the data processes consist of elementary, SQL-like steps, and with each move we get closer to the desired format. In many cases, however, one may need even more developer competence, because to properly set up certain elements custom code might have to be created. This is especially true for Talend, where parameterization is often done by writing Java code.
In terms of integrability capabilities these are able to compete with commercially available ETL tools, but there might be significant discrepancies in performance between individual open-source products, so their potential usage areas are very different.
The best-known and most widespread open-source tools include the products of Pentaho and Talend, which have a free version as well as a licensable edition.
Overview of the MINDSPIRE DELTA Data Migration Tool
We have set up the functionality of our DELTA Data Migration Tool to support our migration methodology, which has already been proven in many projects, according to the needs and expectations of our clients. The solution focuses on the simple and user-friendly parameterization of the transformation rules, for which no or minimal development knowledge is required.
Accordingly, DELTA tool essentially provides the “T” functionality of ETL software. Its main strength is that transformation rules can be set up with simple parameterization using the built-in conversion functions. These rules are not made up of a long and complex chain of elementary steps, as in the case of data loading tools available on the market, but of a one-time binding of the source and target system tables and then the parameterization of the transformation rules between the two.
These can be quite simple copying rules, rules nesting multiple functions, or even quite complex, customizable truth tables. As an input, any data set can be used, which can be source data, previously generated target data, or data generated as a result of intermediate calculations. All this is made possible by a user-friendly parameterization interface, which allows testing the set-up rules immediately, without actually running the procedure.
In contrast to the operation of leading ETL tools, the DELTA data loading solution provides a very simple, transparent interface and functionality, by requiring to declare exactly one transformation rule for each target field. Therefore, both maintenance and “development” activities are significantly simpler, as a small change means altering the parameterization of a rule, rather than comprehending and modifying a complex SQL command sequence at the appropriate point.
The DELTA data migration tool does not attempt to have the widest possible integration capabilities, so its integration capabilities for the source and target systems are limited compared to the leading ETL tools available on the market. DELTA is currently capable to handle multiple file formats and optional relational databases for both source and target systems. However, it can provide this heterogeneously, tailored to the needs of the source and target systems. Furthermore, the tool is completely system and sector independent, practically a transformation framework for business users.
In addition to transformation rules, all other steps require simple parameterization that can be performed by business analysts: the method of the source data loading and exporting transformed data, as well as the workflow describing the entire data stream is very easy to set up and manage. In addition, the process running functions of the DELTA Data Migration Tool support the business analyst approach primarily. At any point in the data streams, it is possible to set up and run the template reports provided by the system to include validation steps, which offer detailed information about the current result of the process at item or aggregate level.
Of course, it is possible and sometimes necessary to create custom scripts and integrate them into data streams, for which developer skills are essential. But with the DELTA data migration solution, the required developer’s competences and expenses are much lower compared to leading ETL tools. In addition, it is an important advantage that the transformation rules are set up by users who understand and know the business needs and processes related to data migration as well, thus the risk of misunderstanding or failure to comprehend the business needs is much lower.
The daily operation of the solution requires basic administrator skills related to standard technologies only, so special and costly training is not required. The use of the DELTA tool knowing the migration process is very intuitive. Only the transformation rules have to be recognized, which are built on SQL commands and simplified for business users.
We basically use the DELTA tool on our projects in the financial sector, which require automatic data migration, and these are very different in size and complexity. We have already implemented smaller migration tasks involving only few products with our self-developed application, but it was also successfully used several times during migration projects at bank acquisitions, when we covered the product range with the DELTA tool.
Comparison of the most common ETL solutions
In the table below, we compare the most common market-leading data loading solutions based on Gartner’s 2021 research and the MIDSPIRE DELTA data migration tool.
Talend and Pentaho have appeared on the market as open-source products, but now these also have licensed versions with much richer functionality. Informatica and Oracle Data Integrator products are only available for a license fee.
The table compares these tools using key parameters such as having a user-friendly interface, available transformation capabilities, process control, customizability, related reporting capabilities, integration capabilities, and performance.
Closing thoughts
Compared to the ETL tools available on the market MINDSPIRE DELTA data migration solution’s strength is that it provides a user-friendly interface and capabilities that enable the complete, even very complex data transformation process (loading, transformation, export) to be executed without developer knowledge.
This has significant added value in areas where the typical workforce consists of analysts and professionals with business knowledge. In addition, the tool also allows to insert custom codes at any point in the process.
Furthermore, DELTA has a wide range of built-in itemized and aggregate reporting capabilities, covering the entire process when needed, that are easy to interpret for business users. According to our knowledge, the customized and parameterizable reconciliation functionality is completely unique on the market.
Its disadvantage may be that its integration capabilities for both the source and target systems currently cover only the basic solutions (file and relational databases), but these can be used in a heterogeneous environment as well.
It has to be also considered, that a licensed environmental component may be required for DELTA to operate. However, the currently targeted financial clientele has this component, so this is not really a real disadvantage.
Do you have a question about the MINDSPIRE DELTA Data Migration Tool? Request a consultation and learn more about the solution!
References
Gartner®, Magic Quadrant™ for Data Integration Tools, Ehtisham Zaidi, Sharat Menon, Robert Thanaraj, Eric Thoo, Nina Showell, August 25, 2021.
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