Before:

A Need for a Partner in Developing Business Intelligence Reporting

Omnigo was in the midst of a major project to build out business intelligence (BI) reporting when the team’s sole data expert left to pursue new opportunities.

The previous BI Director had invested in Sigma’s BI tool to enable timely financial reporting for stakeholders. Unfortunately, the tool was left to languish after his departure. Monthly reporting was being done in a massive spreadsheet with nearly 200K rows of data, multiple columns, and complex calculations, leaving it highly prone to human error and added manual labor.

Meanwhile, Sigma’s robust BI capabilities went unrealized. Gary Schlisner, Omnigo’s CFO, was eager to advance the BI function so the team could easily leverage up-to-date finance insights for better decision-making. Schlisner decided to partner with Data Clymer, a Spaulding Ridge company, to complete the dashboard rollout and accelerate the company’s data strategy.

Solution:

Setting the Stage for Better Operational Efficiency and Automated Capabilities

Rolling out comprehensive dashboards and educating Omigo’s workforce on maximizing Sigma’s BI tool was top priority. We began with a review stage, understanding key components of the business’ current workflows for reporting, better understand current limitations, determine the priority of the dashboards to input into Sigma, and understand the goals and purpose of the dashboards and ROI.

We investigated the existing manual reporting process, reviewing the logic for upsell, renewal, and new logo outcomes. We reviewed data being manipulated within Microsoft Excel, investigating the accuracy and time-consumption of their calculation workflows. This process was crucial to Omnigo, as it helped them locate the differences in reports due to manual error and changes.

After conducting our review, we recommended a modern data stack consisting of Sigma, dbt, Fivetran, and Google BigQuery. 

First, we recreated the logic and calculations that were in the manual Excel spreadsheets/reports, implementing the automated process during implementation. We took ARR reporting data from Salesforce and Netsuite and migrated it into Fivetran, enhancing data freshness.

Within Fivetran, relevant data from the ARR report loaded into Google BigQuery, serving as the central data warehouse. The connection between Fivetran and Google BigQuery enabled data to be stored and managed during the extraction process, offering faster querying capabilities while handling larger volumes of structured and semi-structured data.

The data stored in Google BigQuery connected with dbt, enabling data transformation and modeling. With dbt, we created reusable and modular data models, enabling data cleansing, and apply business logic. The transformed data created solidified the next step in developing a structured and reliable data model for analysis and reporting.

The transformed data moved to Sigma’s BI tool, generating a user-friendly interface for data exploration, visualization, and reporting. Omnigo’s new ability to create accurate dashboards, charts, and other key reports did not require technical knowledge, increasing automated workflows and time-efficiency.

Next, we implemented hard-code fields (term – days and term – months), tables (exchange rates), and defined period vs. immediate transactions of their customer base. This enabled customized visual reports in Sigma to help their team enhance decision-making processes and customer experiences.

Omnigo completed UAT by reviewing their end-of-month reports and sent us variances in dollar amounts to review. We made corrections to the calculations/logic being utilized in the reports until the variances were within an acceptable limit.