reverse ETL

What Is Reverse ETL? Things To Know About This Modern Data Integration Process

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Data Analytics Expert
7 min read

Most associations store their information in an information distribution centre. This data is mostly used by data scientists, engineers, and analysts because of the structure of the extract, transform, and load (ETL) process. These jobs give a valiant effort to give information to other non-information divisions like deals, client achievement, and showcasing. However, these departments that do not deal with data require improved access to data and analytical insights.

Reverse ETL Data integration has the potential to revolutionize this area. New to the modern data ecosystem is reverse ETL, which has the potential to make businesses more data-driven. It allows operational teams to access transformed data in their day-to-day business platforms, such as CRMs, ERPs, and MarTech tools. Everything you must know regarding reverse ETL is in this article.

What Is Reverse ETL?

Data is extracted from a data lake or warehouse using reverse ETL and sent to SaaS applications like CRM, marketing automation, advertising, and customer experience tools. An organization’s most recent, accurate data is aggregated in a data warehouse. It functions as a “single truth source.” However, technical users who know how to write SQL and Python scripts are typically the only ones who can access this data.

Data is transferred from the information/data warehouse into the arbitrator systems that employees use daily through the Reverse ETL procedure. Instead of relying on IT teams or data engineers to process the data, this procedure enables them to obtain the data and insights they require more quickly.

Reverse ETL may also be known as operational analytics or data activation. After data teams have established their modern data stack and have a consistent and automated method for extracting, loading, and transforming data, reverse ETL efforts typically occur. Business users are typically in charge of using the data once it reaches their end platform.

Data teams are also frequently in charge of setting up the pipelines to deliver them to business platforms. In the end, reverse ETL is a method for putting data where the work is already being done, supporting self-service initiatives, and assisting business users in taking real action from their data.

Also Read: Guide To The Best Practices For An Effective Data Strategy

What’s The Difference Between ETL And Reverse ETL?

Consider this brief refresher on traditional ETL for comprehension of reverse ETL. Data integration methodology known as extract, transform, and load (ETL) loads raw data into a target database after transforming it on a secondary processing server.


Extract, load, and transform (ELT) has recently begun to lose ground to ETL due to the popularity of cloud data warehouses. Unlike ETL, ELT data integration does not require data transformation before the loading process. ELT data processing directly imports raw data into a cloud data warehouse. The data warehouse uses SQL pushdowns, Python scripts, and other code to perform data transformations.


ETL and ELT data integration move data into target data warehouses from third-party systems like databases (Oracle, MySQL) and business applications (Hubspot, Salesforce). In any case, with turnaround ETL, the information distribution centre is the source instead of the objective. Third-party software is the target. Data is pulled from the data warehouse, then transformed within the data warehouse to visit the third-force system’s data formatting needs and loaded into the arbitrator system for action in reverse ETL.

Reverse ETL Process

As data warehouses cannot load information straight into a third-party operating system, the process is called reverse ETL rather than reverse ELT. The data must first be transformed to meet the formatting requirements of a third-party operating system. However, this procedure is not a typical ETL because data transformation is carried out within the data warehouse. There is no data transformation “in-between” processing server.

What’s The Process Of Reverse ETL?

Real-time data is delivered to operational and business platforms via reverse ETL solutions (such as MailChimp, Intercom, Salesforce, Zendesk, and others). It is a procedure that transforms your operational and business platforms into data destinations and your data warehouse into a data source. A 360-degree view of customer data can be provided to your front-line teams by making data easily accessible to these platforms.

Personalized marketing campaigns, proactive customer reviews, smart ad targeting, and other applications call for data-driven decision-making. One might ask: After moving the data to data warehouses, why are we placing the data away to the SaaS tools? This is because data warehouses might not always address data silos.

Your data warehouse may isolate your most important business metrics, preventing departments other than data departments from making full use of your data. These departments are heavily dependent on your data teams with traditional ETL. They must request a detailed report from data experts or analysts whenever they need relevant insights. Similarly, when they add a brand-new SaaS tool into the workflow, they depend on the data engineer’s creation of bespoke API connectors.

Due to these issues, your front-line business users may experience slower data access and availability. Fortunately, this gap can be filled by reverse ETL. Your KPIs, such as customer lifetime value, can be synchronized with your operational platforms with the assistance of reverse ETL. It makes sure that your departments can get accurate insights in real-time to make it easier to make decisions based on data.

Why Should Reverse ETL Be Used?

One of the many advantages of reverse ETL is that teams no longer have to seek to find the data they need to make decisions and develop strategies. Instead, they already have the data where they need it in the software and tools. In addition, it is easier to create and maintain KPI alignment across teams, and everyone should have the same business definitions of core metrics. To be more specific, how does reverse-ETL function in practice? Let’s look at three main uses for reverse ETL and real-world examples of what it can do for businesses.

  • Data Is Distributed Beyond The Data Team As A Result

Data teams can use their usual workflow with reverse ETL to send insights from data to other operational business teams. When data is streamed directly from the information/data warehouse to platforms like customer relationship management (CRM), advertising, marketing automation, and ticketing systems for customer support, it becomes accessible and actionable.

Better decisions can be made by providing more in-depth information to the front-line team, like your customer success team. It guarantees that your forefront faculty are furnished with complete knowledge that can assist them with customizing the client experience. For instance, your data science team segmented your weekly updated customer data using intricate modeling. Your customer success team can use reverse ETL to send personalized emails and automatically import this data into an email platform.

  • It Relieves Data Engineers Of The Engineering Burden

Data engineers typically need to construct API connectors to transfer data from the data warehouse to the operational business platforms. There are numerous difficulties associated with these API connectors, including:

  • Data engineers face difficulties in developing and maintaining APIs.
  • The mapping of fields from a source of truth.
  • Real-time data transfer is frequently impossible for these APIs to process.

Reverse ETL is intended to address these difficulties. These reverse ETL tools have built-in connectors as a starting point. Data teams can write and maintain API connectors without this. It’s possible that data teams only wrote a small number of connectors in the past. However, companies can now send data into more systems thanks to reverse ETL’s built-in connectors.

ETL tools also have a visual interface that lets you automatically fill in SaaS fields. You can use reverse ETL tools to define what causes data to move in real time between your operational business platforms and your data warehouse. Consequently, you can free up your data engineers’ time so that they can concentrate on other pressing data issues.

Also Read: How Can Snowflake Integration Enhance The Customer Experience?

  • It Distributes And Automates The Flow Of Data Across Multiple Apps

The manual process of switching between apps to obtain information is eliminated by reverse ETL. At a predetermined frequency, relevant KPIs and metrics are fed to the operational systems by reverse ETL. It can automate numerous workflows in this manner.

Take, for example, the CRM that your sales team uses, Zendesk Sell. They manually track freemium accounts and look for ways to convert them into paid users. For this reason, your record administrators need to bounce to and fro among BI and CRM devices to see where these clients are in the deals pipe. Reverse ETL allows you to import your product data from your data warehouse into Zendesk and alert your account managers whenever a freemium account reaches a certain threshold in your sales funnel.

Although Reverse ETL offers several advantages, the longer-term reward is an enhanced customer experience. Reverse ETL provides contextual information to your customer-facing teams by addressing the issues with ETL. The result is a seamless, individualized service that enhances the customer experience.

What To Look For In A Reverse-ETL Tool?

Even though reverse ETL is required to become truly data-driven in today’s business environment, not all tools are created equal. If you want to ensure you get the best reverse-ETL tool for your business, here are some important things to look for.

  • Reliable Syncing Is Important

A reverse-ETL tool’s most important function is often synchronization. It is what maintains the real-time alignment of all of your data. Your teams and systems might be working with incorrect data if it needs to be fixed. Ensure that syncing is given top priority by your reverse-ETL tool.

  • The Most Recent Security Regulation And Technology

Security and privacy are essential because reverse-ETL tools deal with data. Regulators are also becoming more knowledgeable about digital security, as are our businesses and customers. Businesses must protect their data to avoid penalties, fees, and worse for themselves and their customers.

  • Integrations With Your Tools

It would be best to consider the other tools that a reverse ETL can work with. This is especially true if your teams already use a variety of applications, services, and systems. The apps and services that most reverse-ETL solutions integrate with will be listed. You should list the services you would like to use reverse-ETL and compare that list to the integrations available in a potential reverse-ETL tool.

What Advantages Does Reverse ETL Offer To Various Business Teams?

Reverse ETL can help your various business teams in the following ways:

  • For Sales Teams

Using reverse ETL, sales teams can integrate lead scores into CRM platforms like Salesforce or HubSpot. Take a look at the following scenario: Every week, thousands of people sign up for your website and social media platforms. Some of these leads are keen on your item and have downloaded your free digital book. Now, sales representatives can use reverse ETL to get information about interesting prospects, put this information into their HubSpot/Salesforce client database, and get in touch with them in time. Conversions are also boosted as a result of this.

  • For Marketing Teams

In their Marketing Automation Solution, Marketing Teams have direct access to the frequency with which customers make purchases. Using data on app usage, location, age, job title, and other parameters, they can create more practical roadmaps and effective campaigns. For instance, if most of your customers are on the Facebook platform, your marketing teams can use the customer information in your warehouse to create granular segmentation for the Facebook Ads.

  • For Data Science Teams

Data Science experts can transmit analytics-derived insights to other industries’ teams in their support tools and SaaS platforms. For instance, they can use complex modeling to segment customers and regularly keep them up to date in light of the company’s current goals. These segments can be immediately integrated into CRM sales and marketing platforms for further action and analysis.

  • For Customer Success Teams

The Customer Success Team can use the customer’s product use or previous interactions to send personalized emails and messages. Think about getting a call from a customer who recently signed up for a free trial on your website. They intend to pay for your premium product and want to know its usefulness.

Your Customer Success Team can share the most important information using real-time synchronized data. They can save time by checking users’ product usage, previous billing history, conversations, and current membership to help them or continue from previous conversations.


With reverse ETL, you can sync transformed data stored in your data warehouse with external platforms frequently utilized by marketing, sales, and product teams. It lets you use your data in a completely new way.
Reverse ETL pipelines can help with sophisticated paid marketing, personalization, and, in the end, new ways to use your data. Doing this makes a self-administration examination culture where partners can automatically get the information they need in the spots they need.

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