Kyvos Insights Allows Businesses to Seamlessly Scale Business Intelligence in the Cloud with Kyvos Version 5
New platform update will also empower smarter and more real time data analysis and resource utilization across organizations
LOS GATOS, Calif. – Nov 15, 2018 – Kyvos Insights, a big data analytics company, today announced the availability of Kyvos Version 5, providing businesses with a cloud native way to elastically scale and draw intelligence from exponentially growing data workloads. The platform update delivers enterprise-class OLAP with instant response times and unlimited scalability, allowing enterprises to glean critical insights from today’s largest data sets while also enabling real-time queries to be run on data as soon as it arrives.
The new platform updates have been designed to better allow business users to gain real-time intelligence from ever increasing data sets. Developed specifically for the cloud, the updates expand upon the commitment to scalability inherent in the Kyvos platform by introducing elastic scalability for querying, allowing businesses to scale up and down more seamlessly as data loads change. This elasticity also allows for improved segmentation of data workloads within organizations, meaning different business units can more readily run queries without slowing down other teams.
“As businesses move their Big Data workloads to the cloud, they are faced with the challenge of delivering self-service, interactive BI to their business users. The elastic OLAP capabilities being delivered in Kyvos version 5 allow enterprises to cost-effectively utilize cloud resources and deliver business intelligence with instant response times to users at a scale that was not possible before,” said Ajay Anand, vice president of products at Kyvos Insights.
Kyvos Version 5 updates also allow businesses to run more real-time queries on data before it enters the cube, as well as gain deeper insights on query patterns and data profiles, allowing for the development of smarter data cubes.
Key highlights of the Kyvos Version 5 update include:
- Elastic OLAP designed natively for the cloud: Companies can now more easily and affordably scale up and down elastically with no disruption to deal with peak workloads and usage patterns
- Smarter analytics: Analysis of query patterns provides insights into how data is being used by business analysts, and this is used for auto tuning and guidance for optimized cube design
- Data profiling: Kyvos provides the ability to profile data that is stored in data lakes and use machine learning to optimize how the data can be transformed or added to the cube
“Most large enterprises have either moved applications and/or data to the cloud or plan to move these in the next few years. Kyvos delivers sub-second responses for most queries using almost any size or type of data, making it possible for these enterprises to build high-performing, cost-effective BI on Big Data solutions in the cloud,” said Claudia Imhoff, president of Intelligent Solutions.
To learn more about Kyvos Version 5, click here.
Kyvos Insights is a sponsor of the upcoming AWS re:Invent Conference, taking place Nov. 26-30, 2018 in Las Vegas and will be at booth 116. Members of the media and analyst communities interested in meeting with the company at the conference should contact firstname.lastname@example.org.
About Kyvos Insights
Kyvos Insights is committed to unlocking the power of big data analytics with its unique “OLAP on Hadoop” technology. Backed by years of analytics expertise and a passion for big data, the company aims to revolutionize big data analytics by providing business users with the ability to visualize, explore and analyze big data interactively, working directly on Hadoop. Headquartered in Los Gatos, California, Kyvos Insights was formed by a team of veterans from Yahoo!, Impetus and Intellicus Technologies. The company has partnered with companies including Cloudera, Hortonworks, MapR and Tableau. For more information, visit a www.kyvosinsights.com or connect with us on Twitter and LinkedIn.