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Enterprise Data Operations and Orchestration
Develop and Manage Data Analytics Pipelines and Workflows
The Challenge
Businesses want to redefine their business operations to stay competitive in an increasingly digital world. But they struggle to keep up with the demand for new data analytics use cases in support of constantly evolving business models. BI, AI, and machine learning analytics projects fail to deploy to production because data engineering, operations and orchestration are complex, resource intensive efforts that often take months or even years.
The Solution
Infoworks DataFoundry automates and accelerates the data engineering, operationalization and ongoing management of BI, AI and machine learning workflows from source to consumption, for cloud, on-premise and hybrid environments. We use big data automation to help our customers successfully implement end-to-end analytics use cases to production in days, using 10x fewer people.
Customer Case Studies
- Synchronized with Teradata every 10 mins
- 15 min data-availability service level agreement
- Implemented by 2 engineers in 19 days from requirements to production
| Without Infoworks | Infoworks |
| ~6 Months | 19 Days |
- Streams data from oil wells in near real-time
- Integrates with historical data
- Built a real time drilling dashboard with preventive maintenance analytics
- POC to production ready in 2 weeks
| Without Infoworks | Infoworks |
| ~6 Months | 10 Days |
- 1,500 data sources
- 100,000+ tables
- Ingests, synchronizes and captures changing data on an ongoing basis
- Supports a data shopping cart for enterprise-wide usage
- Eliminated hand coding
| Without Infoworks | Infoworks |
| ~9 months | 2 Weeks |
Automation is the Key
Infoworks DataFoundry is the world’s most comprehensive Enterprise Data Operations and Orchestration (EDO2) system. By applying an unprecedented level of automation to data engineering, operations, and orchestration, Infoworks DataFoundry eliminates big data complexity both on-premise and in the cloud.
Automates the creation of complete data workflows from data ingestion to consumption
Automates promotion and operationalization of data pipelines from dev to test to production
Automates management and monitoring of data pipelines that run across multi-cloud and hybrid environments
Automatically provides independence from underlying big data execution engines and storage platforms
Accelerate Your Path to Diversified Data Analytics
- Deploy new use cases in days….not months
- Add new data sources with a single click
- Enable self-service for faster data pipeline creation
- Choose any big data platform, on-premise or cloud
- Choose any analytics tools, methods, or algorithms
- Integrate custom or 3rd party applications
- Create data pipelines from ingest to consumption
- Manage end-to-end lineage and governance
- Automatically operationalize pipelines at scale
- Adapt to changes in underlying infrastructure
- Add new data sources and execution engines
- Support custom and 3rd party application extensions