Cirro, the company that enables on-demand analysis across all disparate data sources, announced today that it has received a strategic investment from GE Ventures as part of Cirro’s Series A Funding Round which was previously announced October 9, 2013. Their participation follows on the Series A investment led by Toba Capital, Frost Data Capital and Miramar Venture Partners.
Cirro is the Data Federation Hub that seamlessly facilitates the joining of relational, SaaS or Hadoop data while optimizing, orchestrating and managing the overall query processing. Using business intelligence tools already on the desktop, analysts now have the ability to ask questions across their entire data ecosystem. Cirro provides a single point of access to all data regardless of type, size or source enabling the third wave of the Internet revolution in industries.
“We’re pleased to have GE Ventures complete our Series A round of funding,” said Mark Theissen, CEO, Cirro. “Our partnership with GE represents an exciting opportunity for us to investigate many markets where customers are looking to perform fast, on-demand analysis across all their data without the need for traditional ETL or data virtualization.”
“Connecting millions of machines, facilities and networks with advanced sensors means data will exist in many locations and formats. The ability to perform analytics across multiple data sources in different places will offer both new insights and technical challenges,” said Brett May, Head of Business Development and Ventures, GE Software. “Cirro’s innovative approach to federate the processing of analytics gives decision makers new insights through on-demand analytics across any type of data from any source.”
Solving the analytics challenge of integrating data silos across the data center and the cloud, Cirro’s Next Generation Data Federation platform provides a single point-of-access to all enterprise data assets. Seamlessly integrating SaaS, Hadoop, NoSQL and traditional data sources, Cirro enables the querying of multiple real-time and contextual data sources with existing BI tools.
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