Anyone working in the data ecosystem is familiar with ETL or ETL. The process of getting data out of source systems, cleaned and transformed, and then into a data warehouse has been around for decades.
Yet, in our cloud driven world, where the modern data stack dominates, this has been flipped on its head. The rigid, linear data pipelines of old are being closed into loops, where data and insights can flow both ways.
Enter reverse ETL.
Reverse ETL (Extract, Transform & Load) is a process used by businesses to reverse the traditional data transfer process. Instead of extracting data from one source and loading it into a data platform like a data warehouse, reverse ETL takes the same principles, but in the opposite direction. Here, data flows from the data warehouse (most commonly a cloud data warehouse) into applications like a CRM, marketing automation, or other SaaS tools. This helps organizations to ensure data accuracy and gain a more holistic view of their business and customers.
The reverse ETL process starts with identifying the data sources in the cloud data platform that need to flow back into respective applications. These applications can include databases, spreadsheets, text files, SaaS applications, and more. Once the data is identified, reverse ETL extracts it from the cloud data platform, and transforms the data into the format needed for the specific destination. Finally, reverse ETL loads all of the transformed data into the application where it can be analyzed or utilized.
Reverse ETL is a powerful tool for businesses that need to rely on data to power their operations, make decisions, and delight customers. It’s especially powerful for organizations who utilize multiple applications, and want these applications to have the most up to date data. Reverse ETL is used in a variety of industries, including finance, healthcare, retail, education, and more.
Why is reverse ETL important?
Reverse ETL (Extract, Transform and Load) is an important process for any organization that relies on data to drive decisions and actions, especially those that use data in tandem with different business applications to do so. With reverse ETL, the most up to date data continuously and automatically is infused into applications, meaning actions taken in those applications deliver better results. Instead of requiring users to go to a central data platform, reverse ETL brings up to date data directly into the systems, applications, and processes business users already leverage to drive their workflows.
Who is Reverse ETL for?
Reverse ETL is ideal for any data-driven organization, but especially relevant for organizations who have invested in the cloud as part of a modern data strategy. This is because reverse ETL enables them to break the archaic, rigid data pipelines that have prevented the free flow of data from source to platform and back to source.
Organizations can also use reverse ETL to migrate data from on-premises or cloud-based systems back into the source. It can be used when making large-scale changes, such as platform migrations. Reverse ETL is particularly useful for helping companies transition their existing data to new applications and platforms quickly, efficiently, and reliably. By using a reverse ETL to move data back into the source, organizations can ensure that it will remain up to date without needing manual updates or changes.
Differences between ETL and reverse ETL
The main differences lie in how reverse ETL differs from ETL in terms of the order and direction of data flow. The top four differences between reverse ETL and ETL include:
1. Direction of data flow
While traditional ETL and ELT start with the data source and load it into the data platform, reverse ETL begins with data in the data platform, and moves that data into different applications and business productivity tools.
2. Data synchronization
Reverse ETL reverse engineers source systems to ensure accurate synchronization of data, whereas ETL does not synchronize the data in this way.
3. Performance
Reverse ETL also provides better performance in terms of speed and reliability than traditional ETL as reverse engineering source systems is a much faster process.
Best Reverse ETL use cases and examples by industry
Financial Services
Reverse ETL enables financial institutions to integrate data from multiple sources, including core banking systems, customer relationship management (i.e. Salesforce), and accounting systems. This allows the institution to gain a comprehensive view of their customers, helping them better understand customer behavior and prevent customer churn in their financial analytics.
Healthcare
Reverse ETL can be used to integrate patient data from multiple sources such as electronic health records (EHRs) and billing systems. This enables a more streamlined approach to patient care while improving overall data accuracy and quality.
Retail
Reverse ETL can be used to integrate customer data from multiple sources, such as POS systems, loyalty programs, and retail analytics. This allows retailers to gain deeper insights into customer behavior, enabling them to provide more personalized experiences.
Manufacturing
Reverse ETL enables manufacturers to synchronize product data across different systems in order to ensure accurate inventory tracking, order fulfillment, and production scheduling. This helps to streamline the manufacturing process and improve overall efficiency.
Media
Media companies can schedule Reverse ETL processes to send analyzed data and insights into other digital productivity tools (i.e. MS Teams and Slack) to inform the workforce of weekly results as they are on the move. This allows media companies to improve productivity and revenue.
Overall, reverse ETL has the potential to break the rigid, one way data pipelines that have held organizations back from leveraging the full value of their data.
Get your data in the places you need it
If you need to bring data from your cloud data platform into your applications, you need a reverse ETL tool. Ideally, this tool also enables anyone in your organization to find insights in your cloud data with self service analytics, and push those insights into other applications.
With ThoughtSpot Sync, formerly Seekwell, you can not only automatically sync data between your cloud data platform and applications, but sync insights that can be used to drive decisions and trigger action. Try it for yourself today.
