Like all telecommunication giants, Bell Canada relies on vast volumes of data to make accurate business decisions and deliver better services. They use BI tools such as MicroStrategy and Tableau to build dashboards and reports that provide actionable insights on key KPIs. These BI tools work well with small datasets; however as the volume of data increased to billions of rows, they started facing technological challenges and queries took minutes and hours instead of seconds.
They knew they had to remodel their BI infrastructure to move faster and become more flexible to meet the needs of interactive slicing and dicing, drill-down data for self-service analytics on big data of their business teams.
In this session, Big Data leaders from Bell Canada will present why they chose OLAP on Hadoop technology to achieve multi-dimensional analytics and how Kyvos helped revolutionize their analytics by delivering quick results and unlimited scalability on massive data.
- Why adopting OLAP on Hadoop was mission critical for their business teams
- How they exponentially increased the volume and time span of the data they could analyze
- How this new architecture delivers fast performance even with large numbers of concurrent users
- How can you use your existing BI tools to query, slice and dice, drill down, and explore data to gain meaningful insights and support business decisions