What is ‘Datafication’? How This Museum Keeps the Oldest Functioning Computer Running, 5 Easy Steps to Clean Your Virtual Desktop, Women in AI: Reinforcing Sexism and Stereotypes with Tech, Fairness in Machine Learning: Eliminating Data Bias, From Space Missions to Pandemic Monitoring: Remote Healthcare Advances, Business Intelligence: How BI Can Improve Your Company's Processes. (2014). Datafication is a fairly new concept associated with our recent data revolution.But digitalization, a companion concept which captures the impact of … Big Data’s End Run Around Anonymity and Consent (pp. We’re also used to hearing new phrases that both startups and established companies would love us to adopt as industry naming. The term “data”, however, is relatively clear, at least in its contemporary usage. Even more importantly, the process of quantification involves abstraction via the process of turning the flow of social life and social meaning into streams of numbers that can be counted. #    How Can Containerization Help with Project Speed and Efficiency? The Datafication project is about analysing large social media data sets to get usable insights for marketers about how Australian consumers use social media. This term is often employed by scholars seeking to critique such logics and processes. The datafication of employment augurs an acceleration of these forces. Similarly, the mission of this blog is to present a portfolio of tools and technologies that have been used before for data analysis purposes. The Deadly Life of Logistics. doi:10.1177/0163443718818384. However, recent critical work on datafication looks beyond the idea of labour. Here the focus can range from the big corporate players responsible for the bulk of datafication in our lives—Facebook, Apple, Microsoft, Google, and Amazon in the West, and their Chinese counterparts Baidu, Alibaba, Tencent and Xiaomi)—to smaller players across what can be called the “social quantification sector” (Couldry and Mejias, 2018), including hardware, software, platforms, data analytics, data brokerage firms, and even spammers (depending on which country we examine, this sector has more or less close relations with how government at various levels seeks to extract data for monitoring its citizens; China is one country where those relations are particularly close, cf. Minneapolis: University of Minnesota Press. The term “data”, however, is relatively clear, at least in its contemporary usage. Liquifica- Likewise, a process or entity can only be represented in a network if it can be described in terms of the relations that the network can count or process. Big Data and 5G: Where Does This Intersection Lead? Available at: https://www.ibm.com/annualreport/assets/downloads/IBM_Annual_Report_2018.pdf Last accesed: 26 November 2019. In the 21st century, such technologies are powerful environmental forces that shape our self-conception, interactions, and even understandings of reality. The idea of direct learning from data is regarded by many critical data scientists as mythical; it is part of a discourse which critical disciplines have attempted to debunk, as we will see in the next section. Organizations are using them to get benefits. Simply stated, datafication is the set of tools, processes, and technology used to create data-driven organisations and teams. Yet the effects of power that are intrinsic to datafication are often made invisible. This buzzword describes an organizational trend of defining the key to core business operations through a global reliance on data and its related infrastructure. The Information Society, 33(4), 175–191. 143–167). The datafication of HR refers to our increasing ability to use analytics to understand more about our people, HR processes, and external demographics, as well as how they relate to bottom-line business outcomes. Data colonialism, to be exact, is a situation of where datafication has enabled Big Tech to appropriate our data for capitalistic use. Organizations are using them to get benefits. B    In the economic realm, datafication processes are most visible in the proliferation of digital platforms providing a wide range of financial services. Most of these approaches attempt to explain in some way how big data is “made” in terms of its relationship to time, context, and power (Boellstorff, 2013). Leiden: Brill. van Dijck, J. Mejias, 2013) things that cannot be quantified, and so, in principle, cannot be datafied. Is that even proper English? 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