“Our data onboarding to our data lake is streamlined even more than it was before, and it is highly cost-efficient. We are seeing immense savings, more throughput, and we’re seeing more business value come from this platform.”
Andrew Theodore, Head of Data Management and Analytics
“Infoworks has been a great enabler for us at Granicus. With an intuitive UI, we’re able to login and view what is going on with our sources, workflows, and pipelines, making data ingestion to a delta lake easy. On top of that, the Infoworks team has been very responsive and supportive to any questions we have had along the way.”
Rich Mata, Data Scientist
AMN used Infoworks to rapidly build and deploy a new foundational platform that eliminates manual activities through automation and provides an unprecedented level of analytics agility.
We’re honored to be included among this incredible list of innovative companies, products, and individuals.
Infoworks applies intelligent automation across a comprehensive suite of functionality that covers the entire data operations and orchestration workflow to onboard, prepare and operationalize data.
Infoworks provides a complete foundation for enterprises to operate analytics at scale on any cloud, any big data platform, and all types of data
Automate the process for launching analytics and ML use cases to speed deployments.
Reduce dependence on specialized talent through a code-free environment that requires minimal maintenance.
Select the best place to run data operations and applications without recoding.
Manage and orchestrate all data operations in one venue to enable lineage and governance.
Adapt to new business requirements via platform abstraction and API integration.
Data onboarding is the critical first step in operationalizing your data lake. Infoworks not only automates data ingestion but also automates the key functionality that must accompany ingestion to establish a complete foundation for analytics.
A leading healthcare company experienced great success using Infoworks to migrate a analytics workloads to Databricks Unified Analytics Platform in hours as opposed to weeks or months.