Astera introduces the newest addition to the platform, Astera Data Services - a complete API lifecycle management solution. Learn More


What is an ETL Tool: Definition, Uses, and Use-Cases

By |2022-12-16T13:38:05+00:00April 28th, 2020|

An ETL tool is indispensable for a data-driven business, especially if you plan to extract and transform data from several sources before loading it into a centralized repository.

But what is E-T-L, and how does an ETL tool work?

This article will define ETL, when to use it, and how it can benefit your business. Plus, we’ll cover the major types and uses of ETL tools. Lastly, we’ll share a list of critical features that you should look for when choosing an ETL tool for your business.

what is an etl tool

ETL Definition: Getting Down to the Basics

ETL stands for Extract, Transform and Load. It is a three-step data management process that extracts data from structured and unstructured data sources, transforms it into a format satisfying the operational and analytical requirements of the business, and loads it to a target destination.

A well-designed ETL system extracts data, enforces data quality standards, conforms data into a standardized format so that multiple sources can be used together, and delivers data ready to be used by application developers to build applications and business users to make decisions.

Why Do You Need an ETL tool?

Here are some ways in which an ETL tools can help your business grow:

1. Time-Efficiency

An ETL tool allows you to collect, transform, and consolidate data in an automated way. As a result, you can save plenty of time and effort otherwise spent on importing data manually.

2. Handle Complex Data Easily

With time, your business will have to work with a vast amount of complex and diverse data. For instance, you can be a multi-national organization with data from 3 different countries with distinct product names, customer IDs, addresses, etc.

If you have to manage a range of attributes, you may end up formatting data all day long. An ETL tool streamlines the tedious data cleansing tasks for you.

3. Reduced Error Probability

Even if you are careful with your data, you are prone to errors when handling it manually. A slight mistake in the early stages of the data processing can be dicey. Why? Because one error leads to another mistake, and the cycle continues. For example, if you enter sales data incorrectly, your entire calculations can go wrong.

ETL tools automate several parts of a data process, reducing manual intervention and lowering error probability.

4. Improved Business Intelligence And ROI

An ETL tool helps ensure data governance. As a result, you can use this high-quality data to make better decisions and increase your ROI.

what is etl tool - define ETL

Source: AIMultiple

Types of ETL Tools

ETL tools can be categorized into the following main types:

Batch ETL Tools

In this type of ETL tool, batch processing is used to acquire data from the source systems. The data is extracted, transformed, and loaded into the repository in batches of ETL jobs.

It’s a cost-effective method because it uses limited resources in a time-bound way.

Real-Time ETL Tools

Data is extracted, cleansed, enriched, and loaded to the target system in real-time ETL tools. These tools offer you faster access to information and improve time to insights.

As the need to gather and analyze the data in the shortest possible time has augmented, these ETL tools are becoming more popular among businesses.

On-Premise ETL Tools

Many companies operate legacy systems that have both the data and the repository configured on-premise. The main reason behind such an implementation is data security. That’s why companies prefer having an ETL tool deployed on-site.

Cloud ETL Tools

As the name suggests, these tools are deployed on the cloud as various cloud-based applications form an essential part of enterprise architecture. Companies opt for cloud ETL tools to manage data transfer from these applications. Cloud-based ETL tools let businesses leverage flexibility and agility in the ETL process.

Use-Cases of ETL Tools

These are the three most common use-cases of ETL software in the enterprise sector, explaining when to use cloud ETL tools:

Data Warehouse

Data Warehouse is an organized environment that holds critical business data. But before data is loaded into the data warehouse, it has to be cleansed, enriched, and transformed. Once loaded, this data becomes a ‘single source of truth’ for the business.

One of the main steps in building a data warehouse is ensuring that the data retains quality and accuracy. An ETL tool in an on-premise or cloud data warehouse can reinforce this concept and simplify the execution of this use-case effortlessly, allowing reliable data loading.

Data Migration

Another important use-case of an ETL tool is upgrading systems or moving data from a legacy system to a modern one.

The challenge with data migration is mainly the disparity in the format of the old and new systems. An ETL tool, with its enhanced transformation capabilities, ensures the format, structure, and scheme of the source data is compatible with the target system.

ELT or Pushdown Optimization

In an ETL process, transformation occurs in the staging area before data is loaded into the destination system.

On the other hand, in an ELT process, data is fetched, entered into the database, and transformations are performed in the database. This process is preferred for high-volume datasets. It reduces strain on the tool’s server because all the processing is taking place in the database.

Now that you know when to use ETL let’s move on towards looking for when selecting an ETL tool.

What to Look for When Choosing an ETL Tool?

Choosing the right ETL tool for a data-driven business can be an irreplaceable aspect of your data analytics stack. But the question is, how do you find the right tool? Many software development companies offer ETL software that might fit your business needs.

To help you select the right one, we’ve compiled a list of critical features that can narrow down your search:

·       Connectivity

The right ETL tool should connect to all the data sources used by your business. Ideally, it should have built-in connectors for all your required systems, including databases, sales and marketing applications, file formats, and more, making it easier to get any data to and from any system.

·       Easy-To-Use Interface

A bug-free and easy-to-use interface provides a consistent and reliable experience for you when handling data-related tasks. Easy setup is an added benefit that can help you bring your ETL pipelines to life in a matter of minutes.

·       Scalability

As your business grows, your data needs will also expand. Thus, the tool should have performance optimization features, such as pushdown optimization to address your growing business needs.

·       Error-Handling

The ETL tool should handle errors efficiently, ensuring data consistency and accuracy. Plus, it should offer smooth and efficient data transformation capabilities, ensuring zero data loss.

·       Real-Time Data Access

Fetching data in real-time is becoming imperative for businesses to gain timely insights. It should access data from web applications in real-time to ensure faster time-to-insights.

·       Built-In Monitoring

The ETL tools  should have a built-in monitoring system that provides real-time updates on job progress, ensuring smooth process execution.

Wrap Up

Assuming that you now understand what ETL means, it is essential to know that best ETL software helps you get significant insights from data that support your business development. It streamlines and improves blending the raw data distributed across several systems into a data repository. Therefore, selecting the right ETL tool plays a critical role in your business intelligence.

Are you looking for a good data integration tool for your business? Give Astera Centerprise a try!

It is a powerful ETL software that offers support to disparate systems, including REST APIs, SQL Server, MariaDB, SAP HANA, Excel, and more. It supports data manipulation with a range of built-in transformations – in a code-free and drag-and-drop environment.

With an in-built job scheduler, Astera Centerprise allows you to schedule anything from a simple data transformation job to a complex workflow, including numerous sub-flows. You can also push a data transformation job down into a relational database, making the best use of database resources and enhancing performance. Consequently, it helps your better manage processing requirements and increase developer efficiency.


Related Articles

ETL: What It Means and Why Is It Important?

IDC predicts that the sum of global data will grow from 33 zettabytes to 175 zettabytes by 2025. This enormous...
read more

ETL vs ELT: Choosing the Best Approach for Your Data...

The data needs of most organizations have evolved exponentially in the increasingly digital modern world. Businesses these days need to...
read more

How to Select the Right ETL Tool for Business?

A successful data management and BI strategy must answer some key questions, such as: Where does the required information exist?...
read more