کلان داده – سودهای کلان؟ درک ارتباط بین تحلیل کلان داده و نوآوری BIG data – BIG gains? Understanding the link between big data analytics and innovation

1. Introduction The latest technological trends like connected devices and machines, wearables, and the universal application of sensors as well as (user-generated) online content are drivers of a vast and constantly increasing amount of data. In reference to the large volumes of diverse data and associated new data information practices that have become available to firms, big data analytics has become an important topic among practitioners, policy makers and scientists. Broadly speaking, the concept of big data encompasses the amount and complexity of newly available data and the technical challenges of processing them (Dumbill 2013). Depending on the context, big data started to pose challenges to data management along three dimensions: (1) the enormous amount of data (volume), (2) a wide variety of data coming from highly diverse sources (variety), and (3) the pace of data processing (velocity) (Laney 2001). Enormous progress in computing power, storage capacity, and software have been necessary for the surge of big data technologies. Much of the debate and research has centered around possible implications of big data for firms and businesses. As big data alters the sources and types of information available to decision-makers in the firm, it is expected to impact on established ways of decision- and strategy-making which have traditionally relied on predefined data collected for specific needs (Constantiou and Kallinikos 2015). In particular, data which has become available to firms is often not collected intentionally, but in a heterogeneous and unstructured way (Anderson 2008; Varian 2010). The ability to analyze such data, extract insights and appropriate value from it represents a key challenge to firms. One problem big data poses to decision-making is that correlations identified from the raw data are erroneously interpreted as causal relationships or that misleading patterns are found in the data (McAfee and Brynjolfsson 2012; Lazer et al. 2014). Starting from such data patterns found with big data analytics, decisions without potential for improvement or even unwise decisions can be made. That is why the use of big data analytics may not guarantee sustainable, positive effects on firm performance (‘Big Gains’). The gray areas with respect to privacy, data protection, the regulatory environment, or an insufficient internet connection are viewed as the other main barriers to the diffusion of big data and related practices.