What is ETL?

Today, with the immense amount of data coming from so many different sources, we already have alternatives, such as ETL, to extract it, process it, and make it available for today's business demands.

Therefore, using ETL it is possible to optimize data management so that the business analysis team and management can derive value from the data faster.

Read on to get a better understanding of what ETL is, how it came about, what it's for, and what its benefits are.

Understand what ETL is

Extract, transform, and load (ETL) is a process of transforming data from multiple repositories into a unified data warehouse.

It is a traditional method of data transformation where the steps are conducted in the following order:

1) extraction of data from various sources.

2) transformation of data for use.

3) loading data into a single repository.

In the first stage, extraction, data is collected from sources such as spreadsheets, CRMs, data silos, and others, using specific ETL tools and technical support from data engineering and analytics engineering teams.

The data is then transformed into accessible formats with tools, such as dbt, to be finally integrated and uploaded to a centralized repository, such as a cloud or on-premises data warehouse.

How did ETL come about?

ETL is an innovation that gained popularity in the 1970s because it made it possible to centralize information from disparate sources in a single location.

At that time, organizations started working with different databases to store different types of business information. With this advancement, it was necessary to integrate all this data spread across so many repositories.

And it was to solve this problem that ETL emerged, an efficient method of extracting data from different sources, making the necessary transformations, and then loading it into a single database.

This has facilitated the work of analysts, enabling the generation of powerful business insights and more assertive and real-time decision-making.

What is ETL used for?

ETL is used for the strategic team of companies to have a consolidated view of data from different sources and make better business decisions.

It provides critical historical context for the business, facilitates data reliability by making it more accurate, and makes it easier for analysts to find data relevant to their initiatives.

In addition, ETL improves the productivity of data teams because it codes and reuses processes that move data without requiring technical skills to write code or scripts.

6 Benefits of ETL

Here are the top six benefits that the ETL process offers to a company's business.

Time

By using ETL tools, workflows are created and everyone involved is able to perform their duties independently. This fluency streamlines processes and saves time.

In other words, creating a repeatable workflow, which handles multiple automated steps, saves time and eliminates rework when there is any modification to the data.

Transparency

Automated ETL tools can record every step of a company's workflow. As a result, the entire data transformation process is transparent and can be tracked.

Big data

Modern ETL tools can work with very large datasets from disparate sources, both structured and unstructured, in a single mapping.

With the Hadoop tool or similar connectors, for example, ETL allows big data data to be prepared in very large volumes before storing it in data warehouses.

Performance

This is one of the most important benefits of ETL: its ability to ensure fast access to large amounts of data that has already been transformed and integrated.

For example, when BI tools query the database, analysts no longer have to go through the trouble of piecing together records, standardizing formatting, thinking about naming conventions, or performing complex calculations to generate reports. All of this is already done, and the results can be achieved more quickly.

An advanced ETL solution can even incorporate performance-enhancing technologies such as cluster awareness, massively parallel processing, and symmetric multiprocessing, which further increase data warehouse performance.

Data History

The best ETL solutions provide deep insight into historical data, allowing analysts to access reports to see:

• How each result was generated
• Which source systems the data came from
• Where the data was stored in the data warehouse
• how recently it was updated
• how it was extracted and processed etc.

In addition, with ETL you can determine how changes in the data schema may affect reports, and how and where to make adjustments as needed.

Self-service system

By adopting ETL for data transformation, the company can benefit from a self-service system. With it, non-technical teams can access and analyze specific data remotely to make decisions and develop business intelligence.

In addition, in addition to increasing the efficiency and agility of a company, by giving this autonomy to strategic teams, the IT team has more time to optimize and implement solutions.

This is how productivity multiplies and scalability keeps increasing.

Does your business need ETL?

In general, all companies that want to stay competitive need to adopt the most efficient methods and tools, such as ETL.

That's because as data management is becoming more complex, data integration tools also need to be changed to keep pace.

So what are you waiting for?

Start using the full potential of your data now with our state-of-the-art solutions.

Contact us by clicking here.

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