What You Need to Know About Reverse ETL

In order to clearly define reverse ETL, we should first clarify that ETL is an acronym that stands for “extract, transform, load.”

“Extract” refers to the action of pulling out data from many sources. “Transform” is about the cleansing of the data and transforming it into the correct structure and storage format. Then there is “Load,” which is the insertion of data into its new database. 

Those are the three steps of ELT that are used for the data integration process that consists of copying data from one source or multiple sources and centralizing it inside of one singular destination system, such as a data warehouse.

To explain reverse ETL, quite simply, it is the reversal of ETL. In more detail, reverse ETL involves data getting queried from the database and then sending it to marketing tools and to areas of business intelligence to make that data actionable and useful.  

In the grand scheme of things, by using reverse etl, your data stack is complete for an effective workflow. You have your secure data warehouse for data storage, the ability to query and retrieve data with reverse ETL, and a real-time personalization smart hub for your customer data platform to model and activate data in multiple business platforms.

Having the understanding that reverse ETL of moving data warehouse into operational systems, what are the principal use cases for it?  

1. Operational analytics 

One of the more common use cases for reverse ETL is operational analytics, which involves acquiring the data that several teams require and incorporating it into their workflows. 

Operational analytics makes it possible to make more informed decisions and save time with real-time information stemming from their customer data platform. 

This simplifies activities for members of an organization’s team due to the fact that they no longer have to be taught how to read and comprehend business intelligence reports. 

They can just receive the data that is presented to them in an intuitive manner inside the digital workspace that they are already comfortable using. 

2. Data automation 

When an organization is coping with a constant influx of miscellaneous requests for data, it could translate into submitting and fulfilling these requests manually and ending up with a pile of random CSV files. 

Reverse ETL enables data automation to free up those busy human hands that have more impactful ways to spend their time to keep customer’s needs fulfilled. 

What are some examples of data that could be requested by various teams in an organization? 

The accounting team may need the appropriate customer data to add it to the accounting software. Sales teams could be asking for webinar attendee information so they can add these leads to the CRM. 

Over in marketing, they may be asking for data that identifies customers’ purchase history to personalize marketing messages. The support department is requiring the data that indicates the customer accounts that are set up with premium support. 

The product team wants to have a look at the Slack feed of customers who have enabled a particular feature. Finance is ready to use Google Sheets or Excel and is requesting a CSV of transaction data.

Being that the data that an organization’s employees need is ready and waiting in the data warehouse. Reverse ETL makes data automation a simple solution to create a hands-off approach that is automatic as opposed to manual. 

3. Data infrastructure 

The olden days of mass marketing are far less effective when it comes to reaching very specific sections of society that are more hard-wired for certain products and services than the general public. 


The personalization approach to marketing is in high demand for getting quantifiable results. Generic marketing messages aren’t earning companies any appreciation points from potential customers. They prefer messaging that is more customized to who they are and what they enjoy. 


Reverse ETL offers a strong enhancement of customer personalization. Just how specific can reverse ETL get with data infrastructure when it is put into practice? 


What if an online store was interested in reaching out to previous customers that purchased a particular sweater during the Christmas holiday last year? 


Reverse ETL can kick into gear so that the marketing staff can compose an email campaign that is directly meant for those exact same customers. That super-specific purchase data is held inside of the data warehouse, allowing all of those individuals to be reached with a special limited-time offer. 

With its ability to access disparate data sources and personalize customer experiences, reverse ETL is a primary multipurpose piece of data infrastructure and software engineering.

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