Reverse ETL: How to Sync Data Across Any Platform

By  //  March 28, 2022

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Data is one of the most important tools that a company can use to push its business forward and better understand the customer. Improving customer experience and giving departments across a company a source of truth that gives them insight is powerful. 

It can mean the difference between one time, and returning customers. It can also help to focus on the best potential customers so that minimal resources are spent on potential customers that may not follow through. 

This is why finding a way to sync data across any platform in a company is a challenge that’s worth taking on. Finding a way to help every department get the same source of truth will give your people the tools they need to perform the analytics that will push their departments forward. 

The problem is that data isn’t always so easy to maneuver and share across multiple platforms. Finding ways to not only make the data useful but also accessible to the people and departments that need it most is not a new problem that companies are facing. This problem has been around as long as there’s been data to collect on customers. However, thanks to tools like reverse ETL, the solutions to these problems might be more tangible than you would expect. 

What is Reverse ETL?

To better understand what reverse ETL is and how it can help you, let’s cover some of the basics that created the framework for this exciting innovation. Reverse ETL is a new, creative solution to an old, pressing problem, and it’s one that can start to show real-world improvement across a company in big ways. But what is reverse ETL and why is it necessary?

To understand why reverse ETL is necessary, you need to know what ETL is and how it is used. If you aren’t familiar with this terminology, ETL stands for Extract, Transform, and Load. This is a process that was developed as a solution to the age-old problem of data silos. 

ETL, Part of The Solution to Data Silos

A data silo was one of the first major problems that companies had when it came to data acquisition and analytics. These silos represented large storehouses of data that were either unusable or hard to access. This data wouldn’t move out from the silo and into the company in a kind of way, representing a roadblock for analytics. 

That’s when the data warehouse was created as a solution to the ever-present silo problem. These warehouses were locations where data was pulled from a silo, using ETL, and then placed in a centralized location that was then accessible to a company. This created sources of truth that could be pushed out to all departments and data that had been lying dormant was now being utilized to push the company forward. 

Problems With Data Warehouses 

Interestingly enough, as time went on, data continued to accumulate on an unprecedented scale for companies, and this actually lead to a whole new problem. Now, the data warehouse which had originally been a solution to a data silo was becoming a source of challenge when it came to retrieving and using data. 

With data warehouses taking on some of the same problems that plagued data silos, a new and creative solution had to be implemented to help sync data across platforms in a company. That solution is the innovative, and creative implementation of reverse ETL. 

How Does Reverse ETL Work?

With data warehouses problematically taking on characteristics of data silos, finding a solution for how to fix this required some careful examination. Essentially, the data that has been placed in a data warehouse, from a silo had to go through three stages in order to get there, extraction from a silo, transformation into a useful format, and then loading into a data warehouse. 

With warehouses now becoming hard to access, reverse ETL became a solution that made this data accessible. Essentially the data moves back out of the warehouse through a similar path that it entered, however it doesn’t move back to a data silo. Here is where reverse ETL becomes a powerful tool, it actually gets pushed back out to its data source.

A data source is any system that takes in customer data and funnels it into a data warehouse. Using reverse ETL pushes data back out to these data sources where teams can use it to create better customer profiles and improve analytics.

What’s more, is that this data once pushed back out to its data sources, can be enriched by new information, appended, and then sent back to the data warehouse. This acts as not only a retrieval system for important data but also data enrichment. 

Conclusion 

Using reverse ETL provides your company with a creative, effective, and powerful tool to better understand your customers and enrich your data across multiple platforms. This is a new tool in the digital space that is well worth your time to look into.