Big Data Analytics Platform at Nokia – Selecting the Right Tool for the Right Workload

Sponsored, Nassau (NY Hilton)
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Nokia’s Big Data analytics service is strategic to the company. By creating a single data asset, and making it accessible to all, we have opened up new opportunities that range from better decision making to faster innovation. Business units across the company now have the ability to mine Big Data, make data-driven decisions, and analyze trends to drive innovation. The centralized analytics service is a multi-tenant, multi-petabyte environment with terabytes of data flowing in every day. More than 600 internal users access the platform, running an average of 10,000 jobs per day. It serves several general-purpose data processing workloads, as well as traditional business intelligence/data warehousing use cases. The service is made up of an ecosystem of technologies that support business needs, including location content processing, ETL, ad-hoc SQL queries, dashboard generation, and advanced mining and analytics. The service combines commercial and open source components to generate analytical value for Nokia. Technologies such as Calpont InfiniDB for SQL, NoSQL, Scribe, REST, Hadoop, and R form the data and analytics infrastructure at Nokia. In this presentation we will discuss the technology stack of the Big Data analytics service and motivations behind our design choices, challenges we face and future capabilities we are working on.

This session is sponsored by Calpont

Photo of Yekesa Kosuru

Yekesa Kosuru


Yekesa Kosuru is a Distinguished Architect at Nokia. He leads the Data & Analytics engineering team. The team is responsible for building and managing the NoSQL platform and the Big Data Analytics Platform. The NoSQL platform executes hundreds of millions of key-value queries a day and the Big Data Analytics platform hosts multiple petabyte and executes over 10,000 jobs a day, with more than 600 users.

Prior to Nokia, Yekesa worked at Oracle, where he gained deep expertise in relational databases and OLAP technology.

Photo of Jim Tommaney

Jim Tommaney


Jim has extensive experience in leading the development, management, and performance for enterprise data architectures, including clustered, large SMP, and distributed systems for the retail, web, and telecom industries. He is responsible for the architecture, vision, direction, and technical evangelization of InfiniDB. Jim holds a BBA from Texas A&M and a Masters in Management Information Systems from the University of Texas at Dallas.


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