Bringing treasury data into the enterprise analytics conversation

Over the past 20 years in data and analytics, I have spoken with many technology, data, and finance teams about a question that is both simple and complex: how can trusted data be made available to the people who need it, in the tools where they already work?

Many organizations have invested significantly in business intelligence platforms, data warehouses, data lakes, and analytics solutions. At the same time, some high-value data domains remain difficult to integrate. Treasury data is often one of them.

Treasury teams manage information that is essential to understanding liquidity, payments, forecasts, financial costs, and financial risk. Yet this data has often been analyzed in specialist systems, exported manually, or integrated through custom processes maintained by IT and data teams.

This is one reason we built Kyriba Data as a Service, or DaaS. Our goal is to help organizations make Kyriba data more accessible, structured, and easier to use within the corporate analytics platforms they have already chosen. DaaS is not intended to replace enterprise BI tools. It is designed to support them.

Why we built DaaS

When we speak with customers, a common request is to make treasury data easier to access from their own analytics environment. This is reasonable. Organizations want to work with their data in a consistent, governed, and scalable way.

The need is not only technical. Treasury teams increasingly want to combine Kyriba data with ERP, FP&A, bank, payment, working capital, and other financial or operational data. IT teams want to avoid fragile point-to-point integrations and manual exports. BI teams want trusted sources that can be integrated, refreshed, and governed like the rest of the enterprise data estate.

In a survey, we have seen that one in three Kyriba clients has asked for direct access to their data. For us, this is a strong signal. Customers are asking for a better way to include treasury data in their broader analytics strategy.

The broader market is moving in the same direction. PwC’s 2025 Global Treasury Survey found that poor data quality was cited as a top obstacle to forecasting by 76% of respondents. The same survey found that 65% of organizations plan to expand API use for more direct and structured access to financial data. Better decisions require better access to reliable data.

This is consistent with broader enterprise challenges. One study reported that the average large enterprise runs nearly 900 applications, while only 28% are integrated. Other research indicates that executives widely recognize data silos as a business issue.

What DaaS provides

DaaS provides secure access to Kyriba data through standard JDBC connectivity and OAuth2 authentication. For IT and data teams, this means the connection pattern is familiar. If your BI or data platform supports JDBC and OAuth2, it can connect to DaaS.

Just as importantly, DaaS provides data in an analytics-ready structure. Rather than requiring teams to interpret raw operational tables, the data is organized using familiar concepts such as fact tables, dimension tables, and relationship tables.

In practical terms, DaaS separates the data layer from the visualization layer. Kyriba provides governed access to structured treasury data, and your organization decides how to use it in BI, data science, or internal applications.

DaaS also supports incremental refresh patterns. Timestamp fields allow teams to retrieve changes from a prior date instead of repeatedly extracting a full dataset, which helps manage performance, scale, and operational efficiency.

Use cases for IT and treasury

One common use case is enterprise BI / Datawarehouse / Datalake integration. DaaS allows Kyriba data to become another governed source within corporate reporting and analytics environments such as Power BI, Tableau, Qlik, Snowflake, or Databricks.

Another use case is treasury data blending. When Kyriba data can be combined with ERP, FP&A, HR, bank, market, or operational data, organizations can create richer views of financial performance. Cash positions, payments, working capital, and FX exposure can be connected to broader planning.

Historical analysis is also important. Operational systems are often optimized for current business processes, while analytics teams may need a longer view. Because DaaS is built on Kyriba’s Analytics Data Lake, customers can access historical data accumulated over time for trend analysis, long-range forecasting, and for compliance analysis.

DaaS can also support data science and AI initiatives. I mention AI carefully, because its value depends on the quality and structure of the underlying data. With governed, analytics-ready treasury data, teams can more responsibly explore forecasting, anomaly detection, natural-language analytics, and predictive insights.

For Treasury, the value is practical. When Kyriba data is available in corporate BI platforms, treasury teams can analyze liquidity, payments, cash positions, forecasts, and risk alongside ERP, FP&A, and operational data. This helps Treasury contribute to Finance and executive dashboards, while reducing dependence on manual extracts or one-off reporting requests.

A personal perspective

As someone who has spent many years working with data and analytics teams, I know that good data work is often invisible when it is done well. Behind a dashboard, there are many decisions about modeling, security, refresh logic, quality, governance, and performance.

I have a great respect for that work.

With DaaS, our intention is to make part of that work easier and faster. We want to provide a reliable way for IT teams to connect Kyriba data to the analytics platforms they already manage, and to help Treasury data become a first-class part of the enterprise data landscape.

In the end, DaaS is about helping organizations use the data they already have, reduce unnecessary friction, support collaboration between IT and Treasury, and make trusted data available for better decisions.

Read the press announcement about DaaS