Halliburton Case Study

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13

business units with unified analytics

99%

improvement in time-to-insight

Enhanced

data accessibility, governance, and ownership

Region

Americas

Industry

Other

Environment

Hybrid

Solution

Enterprise

Employees

1000+

Previously it would take 2 to 3 weeks to get an answer to an ad-hoc question. By embedding an LLM with Starburst’s data products architecture, data consumers can ask questions in plain language, have it converted to SQL, and get the answer back immediately.

Anonymous, Data Science Leader, Halliburton

13

business units with unified analytics

99%

improvement in time-to-insight

Enhanced

data accessibility, governance, and ownership

About

Halliburton, a century-old leader in oil and gas services, operates globally to provide comprehensive services throughout the lifecycle of oil wells. With 13 independently operating business units and hundreds of data sources, Halliburton faced challenges in managing and utilizing vast amounts of data from disparate locations. To address these issues, the company embarked on a journey to enhance data accessibility, quality, and governance through decentralized data management.

Challenge

Halliburton’s global business units generated substantial high-frequency sensor data stored in various formats and locations, making it difficult to access and utilize effectively. Initial attempts to centralize data in a traditional data lake failed to resolve key issues, including data ownership, quality, and trust. A centralized approach overwhelmed the central team and led to inefficiencies. The company needed a solution to unify these disparate data sources and provide real-time insights to support advanced AI and data science initiatives. The Data Science Leader at Halliburton stated, “We needed a more flexible and decentralized solution to make data accessible and actionable for all users across our organization.”

Solution

Halliburton partnered with Starburst to implement a data mesh architecture, decentralizing data management and aligning data ownership with business units. Starburst data products provide a consistent, logical view of reusable data across various sources, ensuring seamless access to high-quality data.

By integrating large language models (LLMs), Halliburton further democratized data access, enabling users to query data in plain language. The natural language queries are translated into SQL and executed via Starburst, delivering immediate insights without requiring deep technical expertise.

Results

The transition to Starburst’s decentralized data approach resulted in:

Real-time insights across all 13 business units, empowering data-driven decision-making.
Improved data quality and ownership of defined responsibilities among domain-specific teams.
Seamless integration of diverse data sources into a single, logical view, enhancing data accessibility and usability.
Advanced AI capabilities, allowing natural language queries to be translated into accurate SQL for immediate results.
Reduced time-to-insight by 99%, from weeks to minutes.

“The ability to query data in real-time has transformed how we operate. We can now make data-driven decisions faster and more accurately, which is critical in our industry,” the Data Science Leader explained.

Halliburton’s journey showcases how a decentralized data approach, powered by Starburst, can democratize data access, enhance collaboration, and unlock the full potential of organizational data.

More Resources: Open AI and Data Products to Deliver Real-Time Insights at Halliburton with Fahad Ahmad