Data, data everywhere, but if your goal is to provide data to a business analyst rather than a data scientist, what’s the best way to deliver analytics? There are 70+ BI tools in the market and a dozen or more SQL- or OLAP-on-Hadoop open source projects. Mark Madsen and Shant Hovsepian discuss the trade-offs between a number of architectures that provide self-service access to data as well as the pros and cons of architectures, deployment strategies, and customer examples of BI on big data.
Mark Madsen is the global head of architecture at Think Big Analytics where he is responsible for understanding, forecasting, and defining the analytics landscape and architecture. Prior to this he was CEO of Third Nature, where he advised companies on data strategy and technology planning, and vendors on product management. Mark has designed analysis, data collection, and data management infrastructure for companies worldwide.
Shant Hovsepian is a cofounder and CTO of Arcadia Data, where he is responsible for the company’s long-term innovation and technical direction. Previously, Shant was an early member of the engineering team at Teradata, which he joined through the acquisition of Aster Data. Shant interned at Google, where he worked on optimizing the AdWords database, and was a graduate student in computer science at UCLA. He is the coauthor of publications in the areas of modular database design and high-performance storage systems.
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