![]() Social media can also be utilized as a place to gauge a customers psychological profile it's amazing how much information there is in a Facebook like or a Twitter Tweet. The Predictive Sports Book knows that social media can produce a healthy ROI, if done properly. Social media is no longer a vanity platform, but rather it is a place to both connect with current customers as well as court new ones. Connected devices can help with inventory optimization, labor management, marketing, and customer experience, as well as keep its data centers green and its energy use smart. An IoT-connected sports book can make its operations smart. The book details how the five types of analytics-descriptive, diagnostic, predictive, prescriptive, and edge analytics-affect not only the customer journey, but also just about every operating function in the sports book. The Predictive Sports Book reveals how these and other technologies can help shape the customer journey. The Predictive Sports Book is a sports betting company that utilizes the latest technological developments to connect with their customers, while delivering an exceptional personalized experience to each and every one of them. Sports books need to jump aboard this fast moving technology or run the risk of being left behind by their competitors. Today, technology such as AI, Machine Learning, Augmented Reality, IoT, Real-time stream processing, social media, psychometrics, and wearables are radically altering the Customer Experience (CX) landscape. Contra Facebook’s claim to make the web more ‘social’, an investigation of commensuration brings to the fore the question how the social is accounted for in the first place. Online sociality accounts for a model of the social that makes it visible and measurable qua markets inviting data recontextualisation and the creation of value along multiple axes. It is further argued that analytics not just describe but also actively participate in the enactment of social worlds, thereby opening possibilities for new markets or market segments to arise. The analysis thus moves beyond methodological critiques of the utility of Big Data that lack empirical support and specificity. German series xplorer capitaletheringtontechcrunch drivers#In being attentive to the motivations, drivers and challenges engineers face when dealing with Big Data, it is argued that their solutions can enable and support but also constrain specific analytical and transactional capabilities or data flows between various devices and actors. Facebook’s Data Warehousing and Analytics Infrastructure serves as an illustrative example to begin tracing out and describe data assemblages in more detail. It proposes a conceptual framework and demonstrates the empirical potential of a pragmatic approach based on reading published materials and available documentation. This study explores Big Data practices at Facebook through an investigation of the role of commensuration or ‘the transformation of different qualities into a common metric’ in the structuration of analysis and interaction with a major online social media platform. ![]()
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