Announcing Kyvos Version 5: World’s fastest BI on Big Data platform that is revolutionizing Cloud analytics with Elastic OLAP

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Understanding OLAP on Big Data: Why do you need it

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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Tableau rockets through Big Data with Kyvos

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Understanding OLAP on Big Data: Why do you need it

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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Solve your BI Big Data Challenges like Bell Canada did

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Understanding OLAP on Big Data: Why do you need it

Solve your BI Big Data Challenges like Bell Canada did

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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How OLAP on Hadoop helps you increase scale of BI phenomenally?

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OLAP on Big Data

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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