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Creating Strategic Business Value from Big Data Analytics: A Research Framework
Despite the publicity regarding big data and analytics (BDA), the success rate of these projects and strategic value created from them are unclear. Most literature on BDA focuses on how it can be used to enhance tactical organizational capabilities, but very few studies examine its impact on organizational value. Further, we see limited framing of how BDA can create strategic value for the organization. After all, the ultimate success of any BDA project lies in realizing strategic business value, which gives firms a competitive advantage. In this study, we describe the value proposition of BDA by delineating its components. We offer a framing of BDA value by extending existing frameworks of information technology value, then illustrate the framework through BDA applications in practice. The framework is then discussed in terms of its ability to study constructs and relationships that focus on BDA value creation and realization. We also present a problem-oriented view of the framework-where problems in BDA components can give rise to targeted research questions and areas for future study. The framing in this study could help develop a significant research agenda for BDA that can better target research and practice based on effective use of data resources.
Journal Article
The death of the big men and the rise of the big shots
In 1994, the Pacific island village of Matupit was partially destroyed by a volcanic eruption. This study focuses on the subsequent reconstruction and contests over the morality of exchanges that are generative of new forms of social stratification. Such new dynamics of stratification are central to contemporary processes of globalization in the Pacific, and more widely. Through detailed ethnography of the transactions that a displaced people entered into in seeking to rebuild their lives, this book analyses how people re-make sociality in an era of post-colonial neoliberalism without taking either the transformative power of globalization or the resilience of indigenous culture as its starting point. It also contributes to the understanding of the problems of post-disaster reconstruction and development projects.
eBook
Big data : a beginner's introduction
\"Big Data is everywhere. It shapes our lives in more ways than we know and understand. This comprehensive introduction unravels the complex terabytes that will continue to shape our lives in ways imagined and unimagined. Drawing on case studies like Amazon, Facebook, the FIFA World Cup, and the Aadhar scheme, this book looks at how Big Data is changing the way we behave, consume and respond to situations in the digital age. It looks at how big data has the potential to transform disaster management and healthcare, as well as prove to be authoritarian and exploitative in the wrong hands. The latest offering from the authors of Artificial Intelligence: Evolution, Ethics and Public, this accessibly written volume is essential for the researcher in science and technology studies, media and culture studies, public policy and digital humanities, as well as act as a beacon for the general reader to make sense of the digital age\"-- Provided by publisher.
Book
Big Data: Big Data Analysis, Issues and Challenges and Technologies
The data generated at an exponential rate has resulted in Big Data. This data has many characteristics and consists of structured, unstructured, and semi-structured data formats. It contains valuable information for the different types of stakeholders based on their need however it is not possible to meet them with the help of traditional tools and techniques. Here the big data technologies play a crucial role to handle, store, and process this tremendous amount of data in real-time. Big data analytics is used to extract meaningful information or patterns from the voluminous data. It can be further divided into three types i.e. text analytics, audio analytics, video analytics, and social media analytics. Big data analytics if followed by big data analysis process plays a significant role in generating meaningful information from big data. Big data analysis process consists of data acquisition, data storage, data management, data analytics, and finally data visualization. However, it is not simple and brings many challenges that need to be resolved. This paper presents the issues and challenges related to big data, prominent characteristics of big data, big data analytics, big data analysis process, and technologies used for processing the massive data.
Journal Article
Big data : how the information revolution is transforming our lives
Is the Brexit vote successful big data politics or the end of democracy? Why do airlines overbook, and why do banks get it wrong so often? How does big data enable Netflix to forecast a hit, CERN to find the Higgs boson and medics to discover if red wine really is good for you? And how are companies using big data to benefit from smart meters, use advertising that spies on you and develop the gig economy, where workers are managed by the whim of an algorithm? The volumes of data we now access can give unparalleled abilities to make predictions, respond to customer demand and solve problems. But Big Brother's shadow hovers over it. Though big data can set us free and enhance our lives, it has the potential to create an underclass and a totalitarian state. With big data ever-present, you can't afford to ignore it.
Book
Factors Influencing the Adoption of Big Data Analytics in the Digital Transformation Era: Case Study of Jordanian SMEs
Big data (BD) analytics has been increasingly gaining attraction in both practice and theory in light of its opportunities, barriers and expected benefits. In particular, emerging economics view big data analytics as having great importance despite the fact that it has been in a constant struggle with the barriers that prevent its adoption. Thus, this study primarily attempted to determine the drivers of big data analytics in the context of a developing economy, Jordan. The study examined the influence of technological, organizational and environmental factors on big data adoption in the Jordanian SMEs context, using PLS-SEM for the analysis. The empirical results revealed that the relative advantage, complexity, security, top management support, organizational readiness and government support influence the adoption of BD, whilst pressure of competition and compatibility appeared to be of insignificant influence. The findings are expected to contribute to enterprise management and strategic use of data analytics in the present dynamic market environment, for both researcher and practitioner circles concerned with the adoption of big data in developing countries.
Journal Article
