Infoworks.io, the leader in Enterprise Data Operations and Orchestration (EDO2) systems, today announced a significant update to its flagship offering, Infoworks DataFoundry, that extends data source connectivity to support over 190 different source types.
As enterprises move to modernize their analytics, BigQuery is an important option for cloud-based data warehousing. But onboarding your data to BigQuery is more than just data ingestion. Join Infoworks and Google Cloud Platform for this educational webinar, Sept. 16th at 11am PT/ 2pm ET
CEO of Infoworks, Buno Pati sits down with Scott Amyx to discuss his professional background, how Infoworks got started and the challenges that EDO2 systems like Infoworks DataFoundry solves for businesses.
Data onboarding is the critical first step for successfully migrating to a data lake in the cloud. If you do it wrong, you’ll end up with a data swamp.
DataFoundry 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 DataFoundry 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. DataFoundry 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 DataFoundry to migrate a analytics workloads to Databricks Unified Analytics Platform in hours as opposed to weeks or months.