Saama Debuts Fluid Analytics Engine

The platform is sold in support of Saama’s existing suite of Ready Analytics solutions, or as a reusable delivery engine for custom solutions.

saama and data analytics

Saama announced new analytics technology that includes a set of more than 3,000 algorithms to support data science plus a varied set of templates and capabilities for visualization.

The company said the new Fluid Analytics Engine also is fine-tuned to make the most of unlimited cloud resources and Hadoop-built data lakes. The platform was also designed to minimize change management and cost and maximize speed to value, according to Sagar Anisingaraju, chief strategy officer for Saama.

"In our view key drivers for data analytics solutions are speed, business outcomes and reuse. Businesses want to make data driven decisions at the speed of business, with measureable business outcomes," Anisingaraju said. "They want to be able to do this repeatedly for the variety of problems that they are facing."

Anisingaraju said there is growing “big data anxiety” across businesses, as they see their competition emerging with new business models based on data insights. They want to be able to keep up.

"The problem is most of them do not have the basic infrastructure to generate those insights, let alone the analytics programs to integrate those insights to lead their markets with the agility needed," he said.

The new platform is compatible with Saama’s existing suite of Ready Analytics solutions or it can be deployed as a reusable delivery engine customers use to develop custom solutions.

Saama leverages strategic partnerships with Google, Amazon, Hortonworks, Informatica and Tableau to incorporate master data management (MDM), visualization or other technologies as required by the customer.

"One of the key challenges businesses face is being able to produce clean data pipes from disparate sources to advanced analytics solutions," Anisingaraju said. "Today’s data supply chains are much more complex in terms of the variety of data and transient value of it. Businesses struggle to ensure the required data quality for their internal sources as well as for outside sources to make the analytics solutions function at the speed that business wants."

The new Saama platform combines existing assets and new components across the layers of the data stack to furnish a runtime scalable engine. Specifications are defined as a configuration rather than hard coding.

"Today there is a step function going on in implementing data analytics programs," Anisingaraju said. "First the generation of insights, and then using those insights to influence behaviors across businesses. That is going to change as an evolutionary process. In the future, data will no longer be in a raw form, waiting to be processed and analyzed for business to act upon."