P97 Networks Streamlines Reporting with Sigma and Databricks

We chose Sigma because we wanted a scalable reporting platform, built on our Databricks lakehouse, that will allow end users to make data-driven decisions and provide self-service reporting capabilities.
_{—Andrew Crawford, Senior Data Analyst, P97}

Planned Use Cases With Sigma 

P97 is beginning to use Sigma within its web application as a data visualization tool for both its internal and external users. Using embedded analytics, P97’s customers can view a variety of their own data. Right now, P97’s focus is on sharing transactional information to its customers, like fuel and merchandise sales, as well as reporting site connectivity and user information. 

Because P97 is also responsible for fraud mitigation, they show fraud-specific dashboards with KPIs and chargeback trends to customers, along with details of where those chargebacks occurred from the place of transaction and car enrollment. 

Business Outcomes

Before Sigma, P97 data analyst Andrew Crawford described their reporting suite as “a mess.” The team managed over 180 individual reports and datasets, many with overlapping content. The team has since consolidated redundant reports into single Sigma workbooks, using tagging for data source swapping. 

Previously, even minor changes “might mean hours of dataset troubleshooting within the semantic model,” Crawford said. Now, those transformations are controlled by streaming tables within the lakehouse. That means the data transformations are done prior to exposing any data in a report.

Strategic Goals With Sigma 

The overall goal for P97 is to reduce the total cost of ownership for its entire data architecture.  The team’s current priorities include modernizing its reporting suite, delivering near real-time insights, and monetizing self-service access with user tiers. Additional goals include costly search processes with Sigma reports, providing analytics on user behavior, and leveraging one report across many data sources.

With Sigma, the team expects greater report usage, faster BI development, a modernized UI, and significantly reduced report maintenance.

“We chose Sigma because we wanted a scalable reporting platform, built on our Databricks lakehouse, that will allow end users to make data-driven decisions and provide self-service reporting capabilities,” Crawford said. 

Read more about Sigma on Databricks here.

‍