How a Dimensional Data Warehouse Transformed RIA Reporting and Operations

By Steve Kuo and Catherine Quinn

The RIA Simatree supports had built a lot of smart processes over the years, but their data infrastructure hadn't kept pace with their growth. Client data lived in one system, account data in another, financial data somewhere else.  As the firm grew, especially through acquisitions, that complexity only compounded. They needed a partner who could help them build something that would scale.

Building the Right Foundation with Azure

Simatree anchored the entire platform on Microsoft Azure. Azure provided a modern, enterprise-grade cloud environment that could support the full lifecycle of data management, from ingestion and transformation all the way through to reporting and analytics. We stood up a cloud data fabric that would serve as the backbone of every capability that followed.

At the core of the data governance layer, we established a robust framework defining how data would be captured, classified, maintained, and monitored across the organization. Automated data quality exception reports were built to continuously monitor three key source systems for client data, account data, and financial statement data. Any data gaps or referential integrity issues are flagged automatically and routed to the operations team for corrective action, creating a continuous feedback loop that improves data quality over time.

Streamlining Acquisition Integration Through Automation

Growth through acquisition is central to this firm's strategy, and the previous process for integrating a new company's client and account data was a significant operational bottleneck. Simatree worked closely with their integrations team to fully document the existing workflow, map data dependencies across systems, and identify every step where automation was possible.

The result was an automated integration pipeline that dramatically reduced the manual effort required to onboard an acquired firm's data. New acquisitions can now be integrated faster, with fewer errors, and with greater confidence that the data being imported meets the organization's governance standards from day one.

A Dimensional Data Warehouse to Tie It All Together

The engagement culminated in the design and delivery of a full dimensional data warehouse. This data warehouse was built to consolidate all relevant data sources into a single, well-structured environment optimized for reporting and analytics. The dimensional model was chosen deliberately as it allows business users across different teams to query data intuitively, supports complex analytical workloads, and scales as new data sources are added over time.

The warehouse brought together data from client relationships, account performance, and financial outcomes all in one place. Combined with the governance framework and pipelines already in place, the warehouse gave every part of the organization access to accurate, consistent, and timely data for the first time.

Replacing Manual Processes with Power BI and the Data Warehouse

The financial forecasting spreadsheet was one of the most visible pain points and the data warehouse was the key to solving it. Rather than pulling data directly from disconnected source systems, Power BI was connected to the data warehouse as its single reporting layer. This meant that every dashboard and report was drawing from a clean, consolidated, and governed source of truth.

What had once been a laborious, time-consuming process of maintaining a sprawling Excel file became an always-on reporting capability powered by the warehouse. Teams could now pull up accurate, up-to-date financial data at any moment, confident that what they were seeing reflected the full picture.

Today, this firm has a data platform built for the way they actually operate. Clean data, governed processes, automated pipelines, and real-time reporting aren't just infrastructure improvements. They're a competitive advantage.

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