This Global Oil and Gas Leader is one of the largest organizations in the world. The company provides fuel for transportation, energy for heat and light, lubricants to keep engines moving, and petrochemicals used to make everyday items. Its business processes are vast: extracting oil out of the ground, refining it into various fuels and lubricants, transporting products, selling gasoline to service stations, and trading in global energy markets.
“With Informatica Data Engineering solutions, all our decision-makers, analysts, and data scientists have the information they need readily available in a safe, GDPR-compliant environment.”
Principal Data Scientist
- Accommodate a complex, multi-cloud technology environment
- Scale across 4,000+ data sources and 10,000+ data consumers
- Integrate batch or real-time data to meet diverse business requirements
- Streamline decision-making processes, from getting crude oil out of the ground to selling it to 18,000 gas stations in 72 countries
- Consolidate and democratize big data management to reduce costs and minimize reliance on IT
- Connect upstream and downstream data to optimize supply and trading, and manage risk and compliance in a highly regulated industry
- Move beyond ETL and use Informatica Intelligent Data Management solutions to connect to upstream and downstream data sources
- Enable business users and IT to collaborate on data quality processes using Informatica Data Engineering Quality
- Creates a global picture of the company’s energy business to help create business value, enhance compliance, and mitigate risk
- Use Informatica Data Engineering Integration to ingest big data from data lakes on Microsoft Azure and AWS, as well as enterprise applications
- Accelerates decision-making with self-service analytics while increasing scalability, providing a competitive advantage in the global energy marketplace
- Reduces the costs of big data initiatives while giving business users access to high quality, trusted data
Products & Services
Data Engineering Integration
Data Engineering Quality
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