Most organizations nowadays see the massive value potential in (big) data analytics. What most of them still fear is that starting an analytics initiative will result in a massive IT project that will take 12-18 months before first analytical results are achieved – and deploying the results to generate business value will take another 12-18 months.
Enter agile analytics: agile analytics is a rapid approach to experimenting in analytical projects. Model building and advanced analytics is in principle an iterative process. The agile analytics framework focuses on reducing this iteration time so that analysts can provide organizations with better answers more quickly.
In this presentation we will describe a general framework for agile analytics. It involves teams of business users and analysts, requires a fail fast/agile mindset, and drives direct benefits to the business.
We will show a use case done in a big data lab environment. In that case first pre-production results from raw data to a powerful predictive model were generated within four weeks.
Sponsored by Teradata
Dr. Frank Säuberlich is director advanced analytics in the Teradata International Data Science team. His focus is on demand creation across the EMEA and APJ regions. He previously worked at Urban Science International where he was responsible for customer analytics. In this role he has worked with client teams to implement analytical solutions, and he pioneered new types of analysis to improve the efficiency of automotive clients’ marketing efforts. Prior to that, as European customer solutions practice manager he was responsible for the Urban Science Customer Solutions practice in Europe.
While working on his doctoral thesis, he was a scientific assistant at the Institute of Decision Theory and Management Science, University of Karlsruhe, Germany.
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