Fundrise increases data velocity and stakeholder trust with dbt Cloud
This is the story of how Fundrise leverages dbt Cloud to scale its data infrastructure and unlock time for high-impact analysis
in time to introduce new data sources
spent on data pipeline maintenance
A Rapidly Growing Alternative Investment Platform
Fundrise is an investment platform that provides direct access to alternative investments. It has experienced rapid growth over recent years, managing over $3 billion on behalf of more than 400,000 investors.
The company relies heavily on financial data about its investments, assets, and transactions, as well as customer data from its website and app.
Charles Wood, VP of Analytics, explained that their legacy analytics stack had been designed “to be as scrappy as possible and to get the best results we could with minimal overhead.”
However, while this bare-bones set-up was sufficient in the company’s early years, it was never designed to meet the needs of a large organization. With Fundrise’s success came an exponential growth in users, which translated into similar growth in data volume and product complexity.
As the small data team struggled to keep the system functioning under the strain of incoming information, they had to spend an excessive amount of time on maintenance and troubleshooting. It was challenging to innovate or improve, and soon, errors began to creep in.
“Our data wasn’t able to be correct all of the time because of the complexity we added,” explained Charles. “For a little while, we just tried patching things up, but at a certain point, it was clear that our set-up just wasn’t viable.”
Modernizing with a New Data Stack
In dealing with a steady stream of minor errors, the team realized they needed to make changes to ensure consistent and reliable business metrics. Fundrise determined investing in new tools would be more efficient than hiring and training engineers unfamiliar with the company’s unique data needs.
The team chose dbt Cloud to shape data sources in Snowflake, which would then be funneled into Tableau for visualization.
As part of the tooling change, the team took advantage of the opportunity the migration offered to reorganize their data warehouse.
“We made everything unified and organized,” explained Charles. “Doing so using dbt Cloud was much easier than if we had attempted a clean-up without its capabilities.”
As they worked to reorganize the warehouse, the team quickly experienced the benefits of dbt Cloud’s testing capabilities, automatic documentation, lineage tracking, and error alerting—all helpful in freeing up the data team’s time and reducing the amount of troubleshooting needed.
The team’s newfound confidence in the data accuracy and lineage has rebuilt trust and collaboration with users across the business, who previously questioned the quality of the data they were provided.
“On a day-to-day basis, we’re now confident that we’re delivering more data than ever before, that it’s on time, and that it’s correct,” said Charles.
Jack Ploshnick, Fundrise Analytics Manager, continued: “We can do things much faster than we could before, and our stakeholders are confident that the numbers they’re working with are correct. Those two factors really resonate together.”
Time to Focus on Strategic Analysis
Now that Fundrise’s data team spends far less time maintaining pipelines, its analysts can now focus on high-value analysis to answer strategic questions. The business’ data velocity has increased, enabling it to increasingly transition from reactive to proactive work.
“dbt allows us to create new business intelligence dashboards that never existed before,” explained Jack.
He continued: “More importantly, it allows us to spend much less time creating those dashboards and more time on in-depth analysis. We have more time to answer the harder, impactful questions.”
“That benefit can’t be understated,” added Charles. “There was a huge opportunity cost associated with losing out on the highest-value work that we could be doing just to keep the system going. The amount of time we spend on maintenance is almost zero now.”
The marketing team was the first to benefit from the new system and the data team’s new capacity, with a data tool that provided insights into the efficiency of their ads in terms of cost vs. revenue. While this was something the team was able to provide on its previous data stack, the new configuration was much more reliable and time-efficient.
“In the past, we had to check in every day to make sure the marketing attribution numbers were correct and that all the data was flowing through as it was supposed to,” said Jack. “If the data source says that a particular campaign was efficient, we would need to go in and spend time making sure that number was actually right.
“That is now zero work. We know the dashboard is correct. The question now becomes: Why is the marketing program efficient or why is it inefficient? We can finally focus on those kinds of questions.”
The Power of Self-Serve Analytics
One of the major advantages of the modern stack lies in empowering users to work without direct input from the data team at all.
Since the introduction of dbt Cloud, the entire business has seen the ability for users to self-serve their data needs dramatically increase. More and more of Fundrise’s business stakeholders are building their own dashboards without the need for direct supervision or aid from the analytics team.
“We expose the documentation to the stakeholders, and they’re able to confidently do their own analysis,” said Jack. “They weren’t able to before.”
This move towards self-service analytics hasn’t just made Fundrise’s day-to-day operations smoother. Giving analysts access to simple, user-friendly tools has also made hiring and growing the team much easier.
Jack explained: “We don’t have a job title called analytics engineer at Fundrise, because it’s so easy to work with dbt Cloud. If analysts have SQL skills, they can learn dbt. We no longer have to prioritize technical expertise over business savvy, and that’s a huge unlock.”
A Scalable Foundation for the Future of Fundrise
The introduction of dbt Cloud and a modern data stack has allowed Fundrise to scale up and navigate evolving business goals.
For example, while Fundrise initially began as a platform dedicated to real estate investment, over time, the company diversified its offerings. As a result, they introduced a variety of alternative assets and other investment products to their portfolio. This expansion hasn’t been without its challenges, particularly in terms of data management.
The original data model was based on simple one-to-one relationships. However, with the inclusion of multiple new investment products, the data model needed to evolve to accommodate more complex one-to-many relationships.
“Using dbt, we were able to adapt to those changes very quickly. Many of the stakeholders expected a lag between the product change being rolled out and being able to understand the data that was coming in,” explained Jack.
“However, there really was no lag; we were able to adapt almost instantaneously because dbt makes it so easy to make changes to the data model and understand how something upstream affects something downstream.”
What’s Next: Expanding Usage and Governance
No longer swamped by maintenance and troubleshooting, the Fundrise data team is planning for the future. An important part of this vision includes expanding the use of dbt Cloud across more of the company’s teams.
“dbt is currently used by two analytics teams at Fundrise—the product & marketing team and the real estate investing team,” explained Jack. “Our next step is unifying the data landscape across all the different teams in the organization.”
The data team also plans to expand the use of dbt Cloud and leverage its more advanced features for governance such as extended data lineage and access controls.