ETL: Definition, Process and 6 tools


Nowadays it is very common for companies to use multiple databases to store different types of information and it is very likely that more and more are used every day.

When the time comes for a full analysis of that information It is essential to have a Business Intelligence (BI) solution that allows you to integrate all this data in one place.

Integrating the data in a single database allows for better analysis and control of them. For this, it is necessary to have a safe and practical method such as the ETL process (Extraction, Transformation and Loading), which allows organizations to integrate databases in a simple way, by collecting and processing information from multiple systems.

ETL thus becomes a central element of the tools that make up Business Intelligence.

Since its appearance in 1970, the ETL (Extraction, Transform and Load) process is one of the most popular methods for data integration. It was gaining prestige as organizations used multiple databases to store their business information due to the importance of quality data, so the need to integrate that data spread across different warehouses grew rapidly.

If your company has faced this situation, in which a lot of information is stored in different databases, you have come to the right place.

In this article we will tell you what ETL is and how the data integration method works; We will also mention some tools for you to select the most suitable for your business. Let’s start by defining this acronym.

Next, we will talk about the importance it has in the framework of Business Intelligence.

The importance of ETL in Business Intelligence

ETL’s data integration process makes it easy for business companies to analyze and report on data relevant to their strategies, so it also improves productivity by making data easier to read.

ETL is one of the Business Intelligence tools that helps business managers obtain useful data that allows them to make better decisions to carry out their business strategies.

Hence, the importance of ETL is useful for companies by gathering all the information in one place. Among its benefits are:

  1. Greater knowledge of information: ETL helps transform information into knowledge, that is, it helps companies gather a deep domain of their data in one place, which allows the optimization of their processes and the efficiency in decision making.
  2. Improve data accessibility: The ETL process is important for companies looking to have an overview of their data and easy access for data analysis.
  3. Offers reliability: ETL helps to improve the veracity of data and information, so that companies can be sure that the data collected there comply with the regulatory guidelines and standards established by the different audits.
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To take advantage of these benefits it is necessary to implement an appropriate process, so we will talk about it.

The 3 Steps of the ETL Process

The ETL process allows you to improve database performance and consists of three simple steps that will allow you to extract, transform and load multiple data sources to store the latter in a single optimized database.

Let’s see each of them:

1. Extraction

This is a fundamental stage that determines which data sources are to be processed. The speed and order of extraction of this information have a great impact on the entire integration process.

During the extraction of the data from the original source, the ETL process performs an analysis and cleansing of all data, which helps to differentiate it. It is very common that before performing this step, the data comes from different sources and formats such as XML, JSON, CSV and spreadsheet files, SaaS applications, CRM systems, APIs, websites, etc.

The volume of data extracted will depend on the needs of each company.

2. Transformation

At this stage of the ETL process, the data is transformed, all differences that the data may contain are corrected and resolved for better classification. It is carried out through a set of rules that provide the order and clarity with which the data will be integrated into the database and that vary according to the criteria of each company.

Through validation, deduplication, encoding, and filtering in the desired format, this data transformation allows you to know which data has some kind of deficiency to see if it is omitted or set aside for a more in-depth analysis.

3. Loading

Finally, once the data has been extracted and transformed according to the particular needs of the company, the data is loaded into a target database. One of the most common is a centralized data warehouse or repository, either in the cloud or physically in a facility.

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If you are already convinced that you need to implement this method in your company to have a better performance of your databases, consider the following components of the ETL process.

Components of an ETL process

The ETL process saves time in data extraction and preparation for companies. Each of its components helps managers optimize their strategies when analyzing data. The components of an ETL process include:

  1. Compatibility: ETL process loading allows you to determine how often new data will be loaded and existing data will be updated according to previously set parameters through automation.
  2. Audit and registration: It is necessary to have a detailed record of the data that allows guaranteeing the precision in the database and that facilitates the reports and data analysis, in such a way that eliminating errors is simple.
  3. Handling of multiple formats: The sources of the data can be of different origin, either internal such as those from CRM, inventory, finance and human resources, or external such as data from social networks. To extract this data from various sources, the ETL process must handle a wide variety of data formats.
  4. Fault tolerance: ETL systems must be able to recover from any problems that occur in the process and ensure that data moves from one place to another without any difficulty.
  5. Notification support: It is important to know when the data is not accurate, so it is necessary to generate a notification system that alerts you when a problem occurs
  6. Updates: Decision-making in real time is essential to guarantee the success of any company, so the updating of data must be fluid and optimal.
  7. Scalability: As we have said before, as companies grow, information and its databases do too. One of the main components of the ETL process is precisely the performance and throughput of the storage integration necessary to handle rapidly expanding data loads.
  8. Precision: All data must guarantee optimal loading and an accurate information flow that reflects the veracity at each stage of the process.

Finally, we will talk about some tools that could be very helpful to implement this method in your company.

ETL tools are currently available for organizations sophisticated in data integration. Next we will tell you which are the most common:

1. Talend Data Integration

This ETL data integration tool supports different data sources both locally and in the cloud. It allows accessing and transforming any type of data in the cloud or locally. It is an easy-to-use tool, as it provides a simple process for integrating and transforming data through pre-designed integration templates and an extensive library of components.

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2. Xplenty

ETL tools: Xplenty

This ETL data integration platform has a simple and intuitive graphical interface. It helps organize and program data with no-code and low-code options, plus advanced customization and flexibility thanks to its API component.

3. Fivetran


It is an ETL tool that is cloud-based and allows data integration in a personalized way. Build insights from production data with its highly reliable database integration service.

With it you can automatically integrate marketing data, products, sales, finances, etc. In addition, the tool manages the delivery of data from origin to destination and ensures that your database is accurate and always up-to-date.

4. Skyvia

ETL tools: Skyvia

It is an ETL tool that allows integrating data from different bases. It is compatible with different applications in the cloud and does not require much technical knowledge to be able to use it.

It allows two-way data synchronization and duplicate data import, plus it has predefined templates for customizable integration.

5. IRI Voracity

ETL tools: IriThis ETL data integration tool enables data management in the cloud. Although it is not an open source tool, it allows obtaining information from the filtering, classification, union and allocation of data; it also helps transform data quickly.

6. Sprinkle data

ETL Tools: Sprinkle

This platform enables easy and accessible data management and analysis, ensuring faster business decisions can be made.

It has zero code that allows you to assign data types to different warehouse classes, synchronize data from more than 100 different cloud data sources, and upload modified data.

In conclusion, integrating your databases can help you optimize information, having the same space that allows you to quickly identify problems and find solutions more precisely. Choose the integration tool that best suits you and start the ETL process for your company today.

Jerry Gordon

About Jerry Gordon

Webmaster, nature and tech lover. Jerry manages the day-to-day operations at DigiToolsadvisor. He loves enjoying his free time, but most of all, trying new tools to master.