Understanding ETL Processes

When we talk about Data Warehouses e Business intelligence, it is very likely that we will also speak of ETL. It is an acronym (from English: Extract, Transform and Load, that is, Extraction, Transformation and Loading) which names a process that aims to facilitate flows within a Data Warehouse.

Access our previous publication on Data Warehouse.

Data is a very valuable asset of an organization. However, it is relatively common to see companies “lost” in front of the large volume of information. This is due to several factors, in addition to the volume itself. One of the factors is the presence of data from different bases and different sources.

How to analyze a set of data from different systems, which have their own operating logic?

It is in this sense that ETL can help. To understand what ETL is, we need to understand the three pillars that support it (extraction – transformation – load):

• To extract
  
  It means getting data from its original source, which can be varied, such as databases, applications, ERP's, CRM's, etc. Once this data is correctly extracted from its sources, it's time to… 

• Transform
  
  Where basically there is a process of "cleaning" the data, removing duplications, combining them, creating different conditional rules and all the necessary elements so that the data from different sources "speaks the same language", that is, follow the same flow and have the same rules.

• To charge
  
  Once these data are correctly extracted and organized, it's time to load them into their new destination, that is, into a database to receive them.

Image Credits: Grazitti Interactive

The ETL Process

Typically, an ETL tool performs these three steps and is a very important process to ensure that the data needed for reporting and analysis is complete, indexed, and usable. ETL can even help in the dynamics of machine learning and artificial intelligence.

With the popularization of cloud-based tools, where there is supposedly no need for Data Warehouses, questions like: "Even though our company is in the cloud, is ETL still important?" The answer is yes, after all ETL delivers several business benefits that go beyond the simple extraction, cleaning and delivery of data from Point A to Point B, such as:

• Context: helps companies get a deep historical context from their own data; 

• Consolidation: Provides a consolidated view of data, in one place, for more practical and intuitive analysis and reporting; 

• Accuracy: considerably improves data accuracy indices, ensuring compliance with the auditing processes that many companies are subjected to in order to achieve international quality certificates and standards.

How does ETL work?

Despite having different uses and applications, in the traditional way, an ETL tool extracts data from one or several transactional databases, known as OLTP (Online Transaction Processing).

OLTP applications typically contain a large volume of transactional data that, although valuable in the day-to-day business of businesses, is of little use to BI if it is not transformed and integrated.

In this sense, the ETL tool transforms the data, cleaning them, joining them and optimizing them for analysis.

The tool then loads the data into a Decision Support System (DSS) database, or Decision Support System, where BI teams can run queries and present results and reports to company executives to help them make decisions. strategic.

In addition to conventional use (migrating data in an orderly manner to Data Warehouses), ETL tools have been used in different contexts, such as Machine Learning, Artificial Intelligence, Marketing, Migration to Cloud, among others.

Do you think ETL is a tool capable of helping your business grow? We are sure that yes! Fill out our form and we'll schedule a meeting with one of our global experts, no strings attached!