This article discusses how NOV, a global oilfield services corporation, implemented the Databricks Data Intelligence Platform on AWS to enable condition-based maintenance (CBM) strategies for oilfield operations. CBM uses real-time sensor data and analytics to proactively identify potential equipment failures and prevent costly downtime.

Specifically, the article covers:

• The challenges of implementing CBM, such as collecting and processing large volumes of real-time data from sensors, integrating diverse data sources, and dealing with remote locations.
• How the Databricks Data Intelligence Platform on AWS addresses these challenges by providing an open environment for data management, advanced analytics, and machine learning.
• NOV's initial waterfall approach and the transition to an agile, project-based methodology for building Delta Lake and streaming required data.
• Lessons learned, including maintaining data quality, robust monitoring, centralized metadata management, and governance.
• The benefits of using Databricks on AWS for predictive maintenance, reducing downtime, optimizing inventory, and contributing to sustainability through reduced carbon footprint.