Most employees couldn't reach the data without an analyst. Refinery experts now build soft sensors through conversation, no code needed.
A 25,000-person energy company spanning oil and gas, renewables, and retail across more than 20 countries, with over 1,000 AI initiatives in production after eight years of digital transformation that delivered more than a billion euros in cumulative value.
Despite a governed data platform already in place, most day-to-day questions still required an analyst, an IT request, or someone comfortable writing...
“The barriers to data-driven decisions are coming down fast. Our people just need a business question they want to answer, and increasingly they can answer it themselves.”
Repsol is an energy company that specializes in oil and gas exploration, production, and distribution, while also investing in renewable energy solutions.
Databricks is a Big Data company that offers a unified analytics platform for data science, engineering, and analytics teams.
Repsol's Self-service analytics is part of this use case:
Related implementations across industries and use cases
Analysts spent 5 days coding reports. Now, business users query millions of records in plain English for instant results.
Every 'why is this number moving?' queued behind the domain team. Now leaders ask Genie directly and get the answer on the spot.
Complex analytics tools overwhelmed non-technical staff. Now, an AI interface allows employees to query data using simple conversation.
Every 'why is this number moving?' queued behind the domain team. Now leaders ask Genie directly and get the answer on the spot.
Appliance insights bottlenecked through Slack—hours or days, shaped by who you asked. Now product teams query in plain English.
Translations needed line-by-line review; meetings ran one-way through interpreters. Now field expertise flows across languages.
Engineers spent weeks manually mapping well sites. Now, geospatial AI evaluates millions of permutations to maximize leasehold coverage.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.
Most employees couldn't reach the data without an analyst. Refinery experts now build soft sensors through conversation, no code needed.
A 25,000-person energy company spanning oil and gas, renewables, and retail across more than 20 countries, with over 1,000 AI initiatives in production after eight years of digital transformation that delivered more than a billion euros in cumulative value.
Despite a governed data platform already in place, most day-to-day questions still required an analyst, an IT request, or someone comfortable writing...
“The barriers to data-driven decisions are coming down fast. Our people just need a business question they want to answer, and increasingly they can answer it themselves.”
Repsol is an energy company that specializes in oil and gas exploration, production, and distribution, while also investing in renewable energy solutions.
Databricks is a Big Data company that offers a unified analytics platform for data science, engineering, and analytics teams.
Repsol's Self-service analytics is part of this use case:
Related implementations across industries and use cases
Analysts spent 5 days coding reports. Now, business users query millions of records in plain English for instant results.
Every 'why is this number moving?' queued behind the domain team. Now leaders ask Genie directly and get the answer on the spot.
Complex analytics tools overwhelmed non-technical staff. Now, an AI interface allows employees to query data using simple conversation.
Every 'why is this number moving?' queued behind the domain team. Now leaders ask Genie directly and get the answer on the spot.
Appliance insights bottlenecked through Slack—hours or days, shaped by who you asked. Now product teams query in plain English.
Translations needed line-by-line review; meetings ran one-way through interpreters. Now field expertise flows across languages.
Engineers spent weeks manually mapping well sites. Now, geospatial AI evaluates millions of permutations to maximize leasehold coverage.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.