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Oil and Gas Industry
Amazon EMR, Amazon DynamoDB, Amazon Kinesis, Amazon VPC
Enhanced data processing, automated ETL, and reduced costs with scalable AWS solutions
The customer is an oil and gas company owned by the Ministry of Petroleum and Natural Gas, Government of India. Headquartered in New Delhi, it is a public-sector undertaking formed by merging two companies. The company is a diversified energy major with a presence in oil, gas, petrochemicals, and alternative energy sources.
Improved Data Processing Speed
Cost Reduction
Enhanced Performance and Efficiency
The Oil and Gas industry faced challenges in managing application databases, including handling real-time and historical data streams, ensuring scalability for fluctuating workloads, integrating diverse data sources, and maintaining high availability. Additionally, safeguarding sensitive operational data and meeting industry regulations, along with enabling effective data analytics for real-time processing and trend analysis, are critical concerns.
• Amazon EMR processes raw data from Amazon S3, Amazon Aurora, and Kinesis using Apache Spark.
• Multi-stage processing on EMR cleans, transforms, and aggregates data before Redshift load.
• Amazon Managed Workflows automate data ingestion, transformation, and scheduling of Amazon EMR jobs.
• Auto-scaling in Amazon EMR clusters optimizes cost and performance.
• Reserved Instances offer cost savings for long-term workloads.
• Amazon S3 partitioning and bucketing improve query performance.
• Amazon CloudWatch and Amazon EMR logs monitor and resolve job issues.
• Processed data in Amazon Redshift enables fast analytics and reporting.
• Portal users access data from Amazon Redshift for insights and dashboards.
Optimized data processing with a 45% speed boost, automated 60% of ETL processes, reduced compute costs by 50%, improved query performance by 40%, and lowered storage costs by 35% with AWS solutions.
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