Data Integration for Manufacturing and Energy Sectors

Streamline data pipelines across legacy ERP systems, SQL databases, cloud warehouses, and APIs. Etlworks delivers whether you're optimizing operations in a plant or scaling cloud analytics across global energy sites.


Why it matters: Manufacturers and energy providers rely on accurate, timely data to optimize production, reduce downtime, and manage distributed operations. Etlworks bridges legacy systems and modern cloud platforms, enabling smarter decisions and greater efficiency across facilities and geographies.

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Why Etlworks

Hybrid Deployment: Deploy on-premise, in the cloud, or both. Perfect for distributed systems and remote facilities.

Real-Time and Batch: Stream data using CDC or load massive datasets in parallel using batch ETL.

Broad Compatibility: Integrate legacy systems like JD Edwards, SQL Server, and Oracle with modern cloud platforms like Snowflake and Azure.

Firewall-Friendly: Securely move data from remote locations with Etlworks Integration Agent. No need to expose local databases.

Template-Based Automation: Build repeatable pipelines across plants, facilities, or business units with centralized templates and config-driven flows.

Built-In Monitoring: Keep tabs on data movement with real-time dashboards, alerts, and integration with monitoring tools like Grafana.

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How Manufacturing and Energy Companies Use Etlworks

U.S. Silica integrates Oracle, SQL Server, JD Edwards, Quickbase, and multiple APIs into Azure using Etlworks. Their pipelines support high-volume, enterprise-grade workflows with reliability and speed.

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VulkanForms centralizes data from remote manufacturing sites using Etlworks. Their secure ETL pipelines move data from firewalled systems into a central SQL database with no custom code.

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BioUrja Group migrated billions of records to the cloud in just weeks. With Etlworks, they built pipelines from multiple on-prem databases and files into cloud destinations—on time and under budget.

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GEN-I, a global energy trader, uses Etlworks to power high-performance ETL workflows from SQL Server to Snowflake. Advanced partitioning ensures scalable, accurate, and efficient processing.

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