In 2019, offshore drilling contractors, Ensco plc (Ensco) and Rowan Companies plc (Rowan), merged to form Valaris. The newly formed IT team assumed responsibility for an application and data landscape that would double in complexity and size, virtually overnight. Further complicating matters, the data workloads and infrastructure spanned across multiple cloud and on-premise environments, and all assets would migrate to a unified company domain. Unable to take action prior to closing the merge, the team’s challenge was to integrate a large set of data sources as rapidly as possible and provide undisrupted access to data. This required a technology to support migration of existing data assets into Valaris’ new environment, while adding new data assets and maintaining existing data capabilities.
Prior to the merger, Rowan had developed a big data program that encompassed both its industrial IoT and business systems, coupled with context metadata and security. Rowan leveraged DeepIQ’s DataStudio software to ingest more than 2,300 tables from multiple IT sources including commercial and in-house databases into Hive data lake with periodic and automated updates. Rowan also used DeepIQ software to ingest time-series data from its fleet of offshore drilling rigs into their data lake designed to handle 5,000 tags per second for jackups and up to 10,000 tags per second for drillships. Leveraging the data lake, Rowan automated its business intelligence reporting with integrated IT-OT datasets including health, safety, and environment (HSE); drilling performance; supply chain; and finance. Using this platform, Rowan went from monthly reports with a 5-day latency to daily reports refreshed overnight and also achieved 12x improvement in report development speed.
The schema on read strategy employed by Valaris’ data lake delivered the speed and agility necessary to build out the data as a service capability because there was no prerequisite of reconciling all the business system data from both enterprises into a golden data model. Instead, business teams were granted controlled access to any data artifact they required during the integration effort. This decentralized reporting approach created a force multiplier, which allowed for unified business intelligence during the same quarter as the merge.
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