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Modern Treasury Efficiently Scales Data Infrastructure Without a Data Engineer


47% of the team accessing data regularly

3x faster implementation of data stack

Company Size



Marketing, Product, Customer Success, Finance, Engineering

Data Sources


Managing data in a business intelligence tool wasn’t scaling anymore

Modern Treasury, a payment operations platform, achieved substantial growth while managing their data with Chartio, a business intelligence (BI) tool. But as growth continued and more data sources became important to the business, the team needed to transition away from Chartio. 


Data was siloed and it wasn’t possible to create a universal source of truth, interfering with their ability to quickly and accurately answer business questions. Notably, data from their CRM and payment platform couldn’t be joined with the rest of their data.

"We were unable to answer questions that required data from different places. The alternative [to a modern data stack] would be writing these runtime queries in our BI tool, which is expensive, and also messy to do because they’re hard to build upon."

Matt Marcus b&w headshot.png

Matt Marcus

Co-Founder and Chief Product Officer

It was also difficult to pull information on how active customers were in the platform and segment users by other factors, such as whether they were self-serve, on a contract, or on a free trial. And with billing data in another system, it wasn’t possible to correlate payment volume with how much a customer was actually paying Modern Treasury. The workarounds with Chartio required brittle, complicated joins that were prone to failure, and ad-hoc querying would rely on a similar process. 

They began to consider implementing a more robust approach to data management. 

Building a best-in-class data stack with less setup time and resources

Modern Treasury wanted to make sure the next evolution of its data infrastructure would be an effective long-term solution.

"I talked to people who had been through the ringer a bit more and asked them how you set up a data stack properly. One thing that stuck out to me was the importance of being deliberate about how you structure your data. So that way, people will speak a common language, use the same data sources, and use them correctly."

Matt Marcus b&w headshot.png

Matt Marcus

Co-Founder and Chief Product Officer

The team zeroed in on Fivetran and Snowflake as the best-in-class tools they should use for a modern data stack. While they could have built their own data stack with these tools, they chose Mozart Data’s out-of-the-box solution, which uses both Fivetran and Snowflake under the hood. Mozart met their technical needs with less setup time and resources, like a team of data engineers. Mozart would also create custom data connectors for their sources.

"What sold me on Mozart Data was I would not need to really hire data engineers. I could just set stuff up and not have to worry about the underlying providers,” said Marcus. “I’m happy to hire people to work on the architecture of our warehouse, or data science or analytics, but I wanted to avoid hiring data engineers if possible."


With a modern data stack, Modern Treasury was able to set up cleaner, more reliable transforms to join and segment data.

Expanding the use of data to customer success and other teams

After addressing some of their immediate questions, Modern Treasury started focusing on new projects, including cleaning up data models and providing teams with efficient ways to look at a client account.

One example is Modern Treasury needed its customers’ bank account information to be a “one-to-many” for account capabilities. An individual account needs to include multiple data points to describe what it can and cannot do — e.g. “Can this bank account make ACH payments, wire payments, send checks, etc.?” Before Mozart Data, the customer success team couldn’t quickly query this information when communicating with a customer. Mozart Data’s warehouse and transform capabilities enabled the team to adapt their data model so that it could be quickly referenced by less technical members of the team.

"We took our data models and flattened them a lot, and that made the data structure much easier to use. That way our customer success team, or our engineering team, or anyone else, could actually go in and answer questions on their own without writing a really complicated SQL query that would require them to understand the data model."

Matt Marcus b&w headshot.png

Matt Marcus

Co-Founder and Chief Product Officer

Mozart Data’s modern data stack has empowered more employees at Modern Treasury to become self-sufficient and access these improved models, meaning more teams are discovering insights that can drive their work and the business forward. Marketing, Product, Customer Success, and Finance can all pull the data they need. In fact, 47% of Modern Treasury employees query data in a given week.

"We can understand product usage better because people can run reports and explore how people are using our platform. That helps our product managers build better products."

Matt Marcus b&w headshot.png

Matt Marcus

Co-Founder and Chief Product Officer

They’re able to quickly build dashboards for new product feature launches, making it easier to track how their customers are using the product and adopting features.

Marcus also explained, “It helps the customer success managers serve their customers better. They do quarterly business reviews with our customers, and they have a set of reports they create in Looker that they’re able to produce because of the architecture in the warehouse we’ve set up and the data we’ve made available to them. Any CSM can see a dashboard of their customers.”

Digging deeper into their data without rapidly scaling engineering

Modern Treasury has many other ambitious data goals. After scaling for three years without an analytics engineer or data scientist, they filled these positions to help them tackle these new projects. One project is to take non-U.S. currencies and map them to USD, as current models struggle to accurately report on currencies that are not very close to USD in value.

Another goal is to get more revenue and pipeline data, such as where leads are generated and the ratio of marketing qualified to sales qualified leads, into their data warehouse and Looker for easier analysis. They also want to dig deeper into their data on sent and received funds for further insights about their customers.


As Modern Treasury continues to grow, Mozart Data provides the technology and resources to tackle these data challenges and questions without needing to rapidly scale data engineers.

Spend more time on data analysis and less time wrangling your data
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