Williams, a premier provider of large-scale natural gas infrastructure across North America, connects the continent’s growing supply with surging global demand for reliable, cleaner energy. With more than 30,000 miles of pipelines, 6,000 employees, and over 962 commercial customers, Williams manages immense transaction volumes spanning upstream, midstream, and downstream operations. Quick, actionable insights are key to their goal of helping commercial representatives understand customer needs. By implementing Databricks AI/BI Genie, Williams empowered 100+ employees across business areas to better understand customer needs and behaviors faster. The result: democratized analytics, faster answer-turnaround, and a strong data-driven culture that adapts to rapid changes in energy demand and regulatory requirements.
Transforming scattered data into quick insights
Williams operates critical infrastructure supplying approximately 33% of the United States’ natural gas, serving thousands of customers and overseeing millions of rows of data–from contract allocations to granular meter telemetry. Historically, business intelligence was centralized: analysts used tabular perspectives and legacy reporting tools, which became increasingly obsolete as data volumes and demands surged. “We would get requests from executives or business leads—what are our top 25 customers or what was asset utilization last quarter—but each answer required days of coding, iterative validation, and collaboration between technical and non-technical stakeholders,” shares Irma Glover, Commercial Technology Manager at Williams. The challenge intensified as the company expanded analytics enterprise-wide, supporting commercial, regulatory, accounting, and technical services—all needing tailored insights rapidly.
Operational bottlenecks abounded; analysts were inundated with data requests, sometimes spending up to a week compiling complex reports. Beau Galloway, Director Commercial Technology at Williams, explains, “We’re talking millions of transactions and billions of data points, at different velocities—batch, real-time, predictive—all feeding into decision-making. Our legacy pipeline just couldn’t keep up.” Business users lacked direct access and visibility, impacting agility in contract management, asset optimization, and regulatory reporting.
Modernizing data access with Databricks and helping users self-serve
Williams’ journey with Databricks was driven by modernization—not just migrating data but transforming how information is accessed by all stakeholders. Subject matter expert agents called Genie Spaces were built for core domains like contracts, billing, allocations, and geolocation. “We flattened out 27 different tables into large SQL models that Databricks AI/BI Genie could reason over, bringing together all our internal acronyms and business logic,” says Irma. Business concepts were codified into Genie’s instructions, ensuring accurate, context-aware responses.
Powered by Databricks Unity Catalog, and Databricks AI/BI Genie’s natural language querying, data requests now take seconds, not days. Transforming a data request that once took an analyst five days—covering 25 different attributes—Databricks AI/BI Genie completed in only seconds, with validated accuracy. End-users can now work directly with Genie Spaces, asking sophisticated questions and iterating on follow-ups—from “Who are our top 25 customers by revenue in the Northeast for Q1?” to mapping contract usage and rate analysis. Genie’s transparency, surfacing underlying SQL and logic, builds trust and accelerates analytics for technical and non-technical users alike.
Adoption was collaborative: subject matter experts participated from the start, piloting and writing queries, which fostered trust and accelerated buy-in from business stakeholders. “It’s democratization in action—we’re not the bottleneck for insights anymore,” says Irma.
Transformative business impact and future outlook
Since deploying Databricks AI/BI Genie, Williams has experienced transformative impacts. The backlog of data requests dropped from up to ten a week to just one or two, freeing analysts for higher-value initiatives like predictive modeling and enterprise projects. “Our ability to respond to regulatory agencies, executives, and customers alike positions us as a much more capable, agile organization,” notes Beau. Critical insights for operational efficiency, customer engagement, and compliance are now available in minutes, supporting macro-trends such as the surge in electricity demand for AI-powered data centers—a strategic focus for Williams’ commercial teams.
Genie is driving direct revenue: “Without Databricks AI/BI Genie, we wouldn’t have uncovered new market capacities in 2025. It gave us the flexibility to run machine learning and discover commercial opportunities buried in our transactional systems,” says Beau. Easy access ensures broad reach, from customer-facing contributors to high-level executives, and conversational analytics encourage rapid exploration of business trends.
Williams continues expanding Databricks AI/BI Genie for financial planning and pricing while preparing for integration with Microsoft Teams and exploring the simplified Databricks One interface. As Genie’s reach grows, so does Williams’ ability to cultivate a strong data culture. “You foster a strong data culture when insights are at everyone’s fingertips. Databricks AI/BI Genie makes that possible,” says Irma.