01816nas a2200229   4500008004100000022001400041245008000055210006900135260004200204300001000246490000600256520113400262653001401396653001301410653002301423653002001446653002301466100002101489700002001510700001901530856003701549       2018                        eng d  a1927-032100aData Science as an Innovation Challenge: From Big Data to Value Proposition0 aData Science as an Innovation Challenge From Big Data to Value P  aOttawabTalent First Networkc03/2018  a16-250 v83 aAnalyzing “big data” holds huge potential for generating business value. The ongoing advancement of tools and technology over recent years has created a new ecosystem full of opportunities for data-driven innovation. However, as the amount of available data rises to new heights, so too does complexity. Organizations are challenged to create the right contexts, by shaping interfaces and processes, and by asking the right questions to guide the data analysis. Lifting the innovation potential requires teaming and focus to efficiently assign available resources to the most promising initiatives. With reference to the innovation process, this article will concentrate on establishing a process for analytics projects from first ideas to realization (in most cases: a running application). The question we tackle is: what can the practical discourse on big data and analytics learn from innovation management? The insights presented in this article are built on our practical experiences in working with various clients. We will classify analytics projects as well as discuss common innovation barriers along this process. 10aanalytics10abig data10adigital innovation10aidea generation10ainnovation process1 aKayser, Victoria1 aNehrke, Bastian1 aZubovic, Damir  uhttp://timreview.ca/article/1143