As the global economy shifts to accommodate employees working from home, it seems there's more and more focus on "the cloud" than ever before. But does that mean for data companies? And more specifically, how does it impact the functionality and security of an ETL data pipeline? 

In this article, we address all of those concerns, including the distinction between cloud and traditional (or local) ETL, as well as the phases your data experiences in its journey through a cloud-based ETL pipeline. Finally, we'll cover a few of the benefits of performing ETL in the cloud and how you can get the most out of that performance.

Table of Contents

  1. What is ETL?
  2. The Stages of Cloud ETL
  3. Benefits of Cloud ETL Technologies
  4. and Cloud ETL Services

What is ETL?

ETL stands for Extract, Transform, and Load and refers to the collection and aggregation of data from various sources. These may include adverts, social media, emails, databases, or messenger applications. ETL gathers all this data and converts it into a form that allows it to be collated. The data is then moved into a dedicated data warehouse, literally one storage facility dedicated to business data. This allows companies to use all that data to gain profit-boosting insights, without having to trawl through multiple different databases in order to try and see patterns and create reports.

Learn more about what ETL means here.

Cloud-Based ETL vs. Local

Traditional data warehouses are physical servers held in-house. This method is also known as local data management or local data warehousing. Data routes from various sources get cleaned and transformed and are then stored in the physical databanks of these local data warehouses.

Cloud-based ETL services do essentially the same task; however, the data warehouse, and many of the data sources, are now solely online. Cloud ETL tools allow users to manage their data flow via one interface which links to both the data sources and the destination.

The Stages of Cloud ETL

So, what actually happens during each stage of a cloud-based ETL process?


Extraction means pulling data from relevant sources. In traditional data management, this would have been either a manual process or one that had to be painstakingly programmed by a dedicated data management analyst or engineer. Cloud ETL technologies allow users to easily create data pipelines using a visual interface to choose data sources then linking them to the desired destination.


For businesses to use their data effectively, it all needs to work together. For that to happen, the data needs to be transferred into a compatible format that the business can store in a single destination. The transformation process is all about converting and cleaning the data, removing duplicate or erroneous entries, and changing it all into one common format.


The final stage of cloud ETL is to load this data into a cloud-based data warehouse where the business can access all their data whenever it's required.

Some data may be held in a data lake. Unlike a data warehouse, which is a repository for structured data, a data lake contains a pool of often unstructured data, such as texts and emails, which Business Intelligence (BI) tools can trawl for specific keywords or phrases depending upon the requirements of the business. An Arcadia Data Survey suggests that data lakes lead to better business decisions, thanks to discovering key insights faster.

Benefits of Cloud ETL Technologies

The best cloud-based ETL tools allow businesses to manage their own data pipelines with ease and funnel every single bit of required data into one destination from where users can quickly gain useful insights. But, what are the real benefits of cloud ETL vs traditional?

Suitable for More Types of Business

Previously, businesses had to have their data warehouses set up on the premises. These physical servers took up large amounts of space and required physical maintenance which required more staff or hiring external contractors. This could be prohibitive to smaller businesses or those with lower budgets. A cloud ETL service removes the physical requirements of additional space and eliminates the need for additional staff dedicated to data management and server upkeep.

Related Reading: What is a Data Warehouse?

More Cost-Effective

Because cloud-based ETL services are fast and efficient, less time and money gets spent on the data management process. Also, with cloud ETL technologies like, businesses can pay for exactly what they need and change this as business increases or decreases, or when data management needs fluctuate. This makes budgeting and accounting simpler and more cost-effective.

Faster Insights

With an efficient cloud ETL service, changes to data appear almost immediately at the destination. This means that data analysts can pluck out relevant insights much faster, giving businesses the competitive edge they need. and Cloud ETL Services

Businesses who use for their cloud ETL tools regularly comment on how easy it is to use, and how efficiently they are able to not only integrate their data but take useful insights from it almost immediately. also works with other tools like Heroku Connect to help improve Salesforce integration by combining the strengths of various cloud-based tools and applications.

Schedule a conversation with us to find out how cloud-based ETL tools could improve the performance of your business and help you find those key insights faster.