Today’s data teams are under pressure to do more than model data  — they’re expected to enable personalized customer experiences, power business operations in real time, and deliver insights that lead to action. In short, they need to activate their data. But most data still sits idle in the warehouse or behind stale BI dashboards. That’s where reverse ETL comes in.

Reverse ETL (rETL) automatically syncs cleaned, governed, and transformed data from the warehouse into every business tool where action happens. Data teams can operationalize data without manual exports, brittle scripts, or ad hoc integrations.

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rETL increases data team efficiency through automation

As the data landscape evolves, so does the scope of the data team’s responsibility. Building scalable data architecture, managing integrations, and maintaining the warehouse are no longer enough. Today’s teams must also ensure that business users can act on the data, using it to drive decisions and automatically trigger workflows — which leads to higher-quality decision-making and further operational efficiencies. 

rETL improves not only how data flows, but also how data teams operate. With automated rETL, data teams can answer common business team requests like audience creation, pushing lead scores into CRMs, or moving product usage data into support systems — without deploying bespoke scripts; instead, they can count on automation to take care of the gruntwork. This frees up technical talent to work on other data products, data infrastructure capabilities, and pressing priorities — all while ensuring business teams have the data points they need to make decisions and drive growth.

Automated data activation is a foundational part of delivering business value from data — and with rETL capabilities, data teams can not only manage upstream architecture but make downstream impact.

rETL solutions connect data teams to business outcomes

The core value of rETL lies in its ability to put trusted, modeled data directly into the tools business teams use to take action. It’s how data teams turn their work into results that are visible beyond a dashboard. But rETL solutions don’t just move data to help other teams succeed — they elevate the role of the data team too. 

With an automated rETL solution, data teams don’t have to invest countless hours and resources in manually building and maintaining brittle integrations. Instead, they can deliver trusted data to business teams faster, scale impact with fewer resources, and focus on high-value initiatives like modeling, infrastructure, and implementing AI. This then enables teams to extend the reach of the warehouse into day-to-day decision-making, making every insight more timely, actionable, and visible across the org.

And because rETL solutions — like Census — come with built-in observability and governance, data teams also gain visibility into how data is used, ensure consistent definitions across tools, and reduce the risk of versioning issues. They are a streamlined way to activate data and keep it trusted from source to sync — all while ensuring data teams have access to the insights they need to drive impact.

Top data teams amplify impact with rETL practices

rETL shouldn’t require manual monitoring or a team of full-time maintainers. With Census, now part of Fivetran, you get a unified solution designed for scale, reliability, and ease of use. It comes with 200+ no-code connectors, real-time syncs, high-volume throughput, and full observability — so your team stays in control without doing more work.

Take Canva, for example. With over 170 million monthly users and more than 200 terabytes of data in Snowflake, Canva needed to move fast — not just to analyze data, but to activate it. While the data team had already centralized and modeled key data sets, bridging the gap between insight and action remained a challenge.

Marketing teams regularly relied on data engineers to push audience segments into Braze (the company’s email marketing tool) for campaign personalization — a process that could take weeks of manual effort, tying up valuable engineering time and delaying go-to-market timelines.

That’s when Canva turned to Fivetran and Census. Fivetran made it easy to ingest and model data, while Census enabled automated activation — syncing enriched audience segments directly into Braze for real-time personalization. What once took weeks of manual effort to get marketers the audiences they needed could now be done in minutes, resulting in cut API costs, reduced engineering toil, and a 360-degree view of the customer and business. These powerful insights optimize marketing and advertising spend, allowing the company to be more efficient with customer acquisition and retention as a whole.

“Census helps us create audiences and segments and even push machine learning outputs into Braze, or ad platforms such as Facebook and Google Ads. It also means we're not locked into the particular limitations of an individual tool, like a CDP, so we can have a great deal of flexibility.”
— Matthew Castino, Canva

And that is what modern data activation can look like for all industries: fast, trustworthy, and built for impact — because when the right data is always in the right place, your data team stops reacting and starts driving.

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