In this blog, we define reverse ETL and discuss what makes it different than traditional ETL. We provide practical use cases for reverse ETL to show how it can benefit your organization, along with best practices when using this process.

You put a lot of work into cleansing, consolidating, and governing your data to make it valuable for analytical purposes—so why not make it operational in day-to-day workflows so that the whole organization benefits from higher quality, complete data? Reverse ETL, one of the top data and analytics trends of 2022, is not just a trend. It simplifies the process of making data from your warehouse accessible across the company where it is most needed, reducing the need to rely exclusively on using point-to-point integrations.

What is Reverse ETL and How is it Different Than Traditional ETL?

Reverse ETL is the process of taking unified, transformed data found in a data warehouse and bringing it back into one or more operational source systems and enterprise applications so it can be used natively by business users in their day-to-day workflows and processes.

While traditional ETL is responsible for extracting data from source systems, transforming it (cleansing the data to fit business and analytical requirements), and loading it into a central data repository tuned for analytics, reverse ETL is responsible for the opposite—going “backward”. It pulls data from the central analytics data repository, applies necessary transformations for compatibility, and loads it back into your operational systems.

Diagram of how reverse ETL brings the modern data stack full circle, including white boxes of different tools and platforms over a black background.

Reverse ETL enables you to operationalize your data, reduce redundant processes, automate your data, improve data governance, eliminate point-to-point integrations, and enhance customer experiences. Photo: Hightouch

What Are Examples of Use Cases for Reverse ETL?

The best way to know if reverse ETL is the right solution for your business is to understand practical ways it can be applied. Here are a few examples of how implementing reverse ETL improves the way companies do business.

  • Sales and Marketing: These two lines of business have intertwined activities and campaigns, but they often use different applications, platforms, and systems for their day-to-day operations. Even if the data from these systems are brought together in a data warehouse, they typically are only used for historical reporting.With reverse ETL, these different business units can have data synchronized across their multiple systems, enabling sales and marketing team members to gain a more holistic view of customers, and how collaborative efforts positively affect those customers. This access to information can enable more personalized marketing and increase conversion rate and sales.
  • Customer Service: Ensuring customer service reps have access to up-to-date, actionable customer data is the key to ensuring a great customer experience. Reverse ETL can help bring together data from various platforms and systems—customer profile, history, notes, etc.,—directly into the platforms that customer service reps use when engaging with customers.
  • Human Resources: Organizations are focused on employee satisfaction and engagement as they look to retain their workforce. Reverse ETL can provide instant access to human resource applications and systems information from a variety of sources that an HR manager may not otherwise have. This data can help enhance the employee review process, alert to retention issues, or detail an employee’s level of engagement. With automated processes, an HR manager can have access to data instantly instead of having to go to various systems and collect it, freeing them up to focus on other tasks.

What are the Benefits of Reverse ETL?

In many organizations, the most actionable information can be found in the data warehouse—the data repository for the “single source of truth”. With reverse ETL, this actionable information is found directly in business applications so that insights are uncovered more intuitively. For example, you can tap directly into a:

  • B2B application that offered custom suggestions for new purchases based on CRM or ERP data.
  • B2C application that offered additional incentives for customers deemed potential long-term buyers from various third-party applications and proprietary application sources?

Some benefits of reverse ETL:

  • Operationalize Data: Organizations can operationalize their curated data for analysis and feed it directly to third-party applications or other similar systems. This gives service reps, marketing, and other business groups insights only analytical data can provide to drive sales and customer satisfaction.
  • Reduce Redundant Processes: Organizations can keep a “single source of truth”, such as a data warehouse or data lake, by feeding that data to source systems instead of creating siloed and ad-hoc data processes to resemble or match existing analytical data.
  • Automation of Data: It’s common for business units to request a CSV only to upload that data into applications or other similar systems. Reverse ETL can automate this process, improving timeliness and reducing errors.
  • Improved Data Governance: With reverse ETL you can use calculations, naming conventions, and other methodologies already applied to existing analytical data in your applications. By taking data out of a source system, transforming it, and immediately adding it back in, you remove the need to recreate data governance rules. Your logic can be applied in one place and used everywhere.
  • Elimination of Point-to-Point Integrations: It’s common for an organization to have tens, maybe even hundreds, of applications in their workflow across all business units. Being able to pull the data from one central location to feed these applications will eliminate the need for point-to-point integrations that certain third-party applications try to provide.
  • Enhance Customer Experiences: Customers can almost immediately benefit from incorporating reverse ETL into customer-facing applications or the applications businesses use to interact with customers and clients. Representatives and applications can immediately respond to customers using individualized customer data—creating an enhanced, personal experience.

Want to learn more? Schedule a free 30-minute consultation with one of our reverse ETL experts.

Best Practices for Implementing Reverse ETL

There are a handful of reverse ETL tools on the market, including Census, Grouparoo, and Hightouch. You can also build your own implementation of reverse ETL using nearly any programming language and APIs for specific vendors and applications.

While most use cases for businesses can be met with out-of-the-box reverse ETL tools, there are instances where an in-house tool may be a better approach. For example, you could leverage a variety of APIs and vendor-built utility tools, such as the bcp utility from Microsoft, to build a custom tool that serves data from the warehouse to their applications. Applications like Salesforce, Dynamics 365, and Hubspot, to name a few, all have API endpoints to develop on and create this custom-built reverse ETL. This provides organizations with flexibility and security for specific use cases that current tools on the market do not provide.

Whether an in-house or market-bought tool, there are some best practices to consider when deciding which tool and feature set is right for your business:

  • Connectors: One of the biggest advantages of reverse ETL is it allows you to provide the highest quality data to SaaS platforms. However, if you’re using a tool that can’t easily connect to those platforms, then the benefit is lost. When deciding on your tool, make sure to identify the platforms you need to connect to and how the data will be loaded into these platforms. Don’t forget your organization’s own proprietary applications and APIs.
  • Automated Syncing: Once data has been loaded into a third-party platform, the ability to keep the data fresh and synced to all your different systems is vital to getting the best value out of a reverse ETL tool. When choosing your tool, make sure it has the capability to keep data synced automatically across all systems.
  • Security: Sharing data across an organization presents risk when dealing with personally identifiable information (PII), HIPAA (health care) regulations, and other sensitive data. When dealing with this type of data, encryption at rest and in-transit is necessary. In addition to encryption, the reverse ETL tool shouldn’t retain data longer than is needed to load the data. Within the tool itself there needs to be strong role base access control (RBAC) to ensure sensitive data can’t accidently be moved somewhere it could be exposed.
  • Fault Tolerance: Make sure the reverse ETL tool your business adopts prevents loss of data when a network failure occurs. First, you want to make sure the data is loaded correctly, so should a failure occur, your tool should resume the process and ensure the remaining data is loaded into the system as expected.
  • Auditing: It’s important to pick a tool that allows for auditing reverse ETL pipelines for issues and debugging purposes. When there is a clear picture of how data is moved from a data repository to the target platform or system, there is increased confidence in the data.

Most of the reverse ETL tools on the market already provide many of these best practice features, making adopting this into your organization’s data culture easy.

Building the Case for Reverse ETL

As you continue to adopt new systems and applications to meet your organization’s growing data needs, reverse ETL can help streamline serving those applications and systems with data faster and cheaper. It’s true that other solutions with similar functionality exist—such as a Customer Data Platform (CDP) and iPaaS solutions—but reverse ETL is the only solution that helps unlock data across your organization and allows for business users of various platforms, systems, and applications to react in real-time with customers and with each other—driving more value out of your organization’s data.

John Bemenderfer John is a Senior Consultant based out of our Dallas office. He has experience across the entire data stack, from data engineering to analytics, helping clients get the most value out of their data. He also helps lead the Power BI practice for Analytics8. Outside of work, John enjoys spending time with his daughter and wife, dungeons and dragons, and anything Star Wars related.
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