Today we are excited to launch Kyvos Version 5. Our latest release is a next-generation BI on Big Data platform that revolutionizes analytics in the cloud or on-premise Big Data platforms through its next-generation OLAP technology. Curated for enterprises who need to examine their Big Data deeply and leverage it to build competitive advantage, Kyvos 5 will enable enterprises to conduct smarter, faster and more cost-effective analytics on their Big Data platforms.
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Planning to be at the upcoming AWS re:Invent conference? Meet us at booth 116 to learn how you can build your big data analytics cloud platform that delivers instant insights on trillions of rows of data.
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Tableau Conference 2018, a flagship event where Tableau partners, customers, and technology enthusiasts come together to discover and discuss ways in which Tableau can be used for business analytics, was held in Las Vegas from October 22-25. At the conference this year, Kyvos showcased how it works with Tableau to deliver fastest insights on Big Data in the cloud and on-premise platforms.
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A futuristic data strategy is important for your organization if you want to truly access your data lake for business benefits. As more and more data gets generated, it becomes challenging to meet the reporting needs of the business stakeholders who want reports with more dimensions, metrics, and measures. Your existing systems cannot deal with such massive amounts of data as they’re not built for that, and thus you should explore new technologies that have been specifically built to solve your BI Big Data challenges.
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If you have built your Big Data platform in the cloud or in an on-premise environment, but find it difficult to extract insights when you need them, then you must read this article to explore how OLAP on Big Data technology can help you overcome the challenges of speed and scale associated with traditional BI approaches.
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With high-velocity data coming in from a wide variety of sources, implementing a big data stack makes sense but does it solve all your data problems? Having all your data on Hadoop, without being able to access it through a BI (Business Intelligence) platform is like keeping your data in a cold storage till it loses its sheen.
Storing rich historical data on Hadoop is the first step but once you have it all in one place, it becomes necessary to make it accessible to all the stakeholders who need it.
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