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Bell Canada to Present Why They Chose Kyvos’ OLAP Technology for Business Intelligence on Big Data at New York’s Strata Data Conference

Bell Canada to present their journey of Big Data analytics and how they were able to achieve interactive BI at a massive scale

NEW YORK, Sept. 7, 2018 – Kyvos Insights, a big data analytics company, today announced it will be hosting a session with Bell Canada during Strata Data Conference in New York, the leading event for the data industry visionaries.

The session on “How Bell Canada increased the scale of BI exponentially with OLAP on big data” will feature insights from Mark Huang, director of engineering at Bell Canada, and Ajay Anand, vice president of products and marketing at Kyvos Insights. The session will provide a deep dive into why Bell Canada chose Kyvos’ OLAP on big data technology to achieve interactive multi-dimensional analytics and how it helped the company deliver to its growing business intelligence demands.

“As companies grow, their data programs and business intelligence initiatives need to evolve to meet changing organizational demands. However, while data teams appreciate this need to grow, finding an architecture which is truly scalable, while delivering interactive response times, remains a constant challenge,” said Ajay Anand, vice president of products and marketing at Kyvos Insights. “We’re honored that Bell Canada has chosen Kyvos Insights to help them scale their leading business intelligence initiative to achieve their business objectives.”

Along with discussing the business value driven by the implementation of Kyvos Insights’ technology, the session will also explore:

  • Why adopting OLAP on big data was mission-critical for their business teams
  • How Bell Canada exponentially increased the volume and time span of the data they could analyze
  • The importance of selecting an architecture that delivers fast performance with an increasing amount of concurrent users

“We’re thrilled with the results we’ve been able to achieve through our implementation of Kyvos Insights,” said Mark Huang, director of engineering at Bell Canada. “Large volumes of data are what allows us to make the right business decisions for our company and enables us to deliver the service our customers expect. We’re excited to continue partnering with Kyvos Insights to further unleash big data to drive business insights.”

Complete session details are below:

Mark Huang

Mark is the Director of Data Engineering atBell Canada. Mark’s responsibilities include managing BI environments, ETL development, architecture, governance, and technology decisions. Since joining Bell over 6 years ago Mark has played a key role in designing the BI roadmap and executing the strategy to meet current and future business needs.

Ajay Anand

Ajay is the vice president of products & marketing at Kyvos Insights. His association with Hadoop goes back to 2007 when he was director of product management at Yahoo and led their initial Hadoop projects and releases, after which he founded Datameer. Ajay also held product management and market development roles at SGI and Sun. Ajay earned an M.B.A. and an M.S. in computer engineering from the University of Texas at Austin and a BSEE from the Indian Institute of Technology.

The world’s fastest BI on big data platform, Kyvos enables organizations to create a BI Consumption Layer that allows organizations to create data cubes with near limitless scalability and performance. To learn more about Kyvos visit www.kyvosinsights.com or request a demonstration at: www.kyvosinsights.com/request-demo

About Kyvos Insights

Kyvos is a modern, cloud-native analytics acceleration platform that enables sub-second querying on massive datasets. The platform’s universal semantic layer democratizes data across the enterprise through self-serve analytics. You can instantly analyze data at any scale irrespective of the analytics tool or underlying cloud platform. For more information For more information, visit us at www.kyvosinsights.com. or connect with us on Twitter and LinkedIn.

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