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"Carefully distinguishing between big data and open data, and exploring various data infrastructures, Kitchin vividly illustrates how the data landscape is rapidly changing and calls for a revolution in how we think about data." - Evelyn Ruppert, Goldsmiths, University of London "Deconstructs the hype around the ‘data revolution’ to carefully guide us through the histories and the futures of ‘big data.’ The book skilfully engages with debates from across the humanities, social sciences, and sciences in order to produce a critical account of how data are enmeshed into enormous social, economic, and political changes that are taking place." - Mark Graham, University of Oxford Traditionally, data has been a scarce commodity which, given its value, has been either jealously guarded or expensively traded. In recent years, technological developments and political lobbying have turned this position on its head. Data now flow as a deep and wide torrent, are low in cost and supported by robust infrastructures, and are increasingly open and accessible. A data revolution is underway, one that is already reshaping how knowledge is produced, business conducted, and governance enacted, as well as raising many questions concerning surveillance, privacy, security, profiling, social sorting, and intellectual property rights. In contrast to the hype and hubris of much media and business coverage, The Data Revolution provides a synoptic and critical analysis of the emerging data landscape. Accessible in style, the book provides: A synoptic overview of big data, open data and data infrastructures An introduction to thinking conceptually about data, data infrastructures, data analytics and data markets Acritical discussion of the technical shortcomings and the social, political and ethical consequences of the data revolution An analysis of the implications of the data revolution to academic, business and government practices
This invaluable guide places XML in context, discussing why it is so significant, and how it affects the business and computing worlds, most recently with the emergence of Web services. It also explores the full ranges of XML related technologies.
In this report, CSIS and JICA-RI analyze the challenges and opportunities that exist in the pursuit of the “data revolution” called for by the UN High-Level Panel of Eminent Persons on the Post-2015 Development Agenda.
The book presents a nuanced narrative about statistical development in Africa since around the time of independence when emerging states needed statistics mainly to support their planning processes. It highlights challenges faced then, some of which have persisted, including institutional, organizational and technical challenges. These challenges manifest themselves in countries with different degrees of severity and are quite severe in post-conflict countries. Key statistical programmes to support statistical development in Africa in the 1970s, 1980s and 1990s are presented
Exploit the power and potential of Big Data to revolutionizebusiness outcomes Big Data Revolution is a guide to improving performance,making better decisions, and transforming business through theeffective use of Big Data. In this collaborative work by an IBMVice President of Big Data Products and an Oxford Research Fellow,this book presents inside stories that demonstrate the power andpotential of Big Data within the business realm. Readers are guidedthrough tried-and-true methodologies for getting more out of data,and using it to the utmost advantage. This book describes the majortrends emerging in the field, the pitfalls and triumphs beingexperienced, and the many considerations surrounding Big Data, allwhile guiding readers toward better decision making from theperspective of a data scientist. Companies are generating data faster than ever before, andmanaging that data has become a major challenge. With the rightstrategy, Big Data can be a powerful tool for creating effectivebusiness solutions – but deep understanding is key whenapplying it to individual business needs. Big DataRevolution provides the insight executives need to incorporateBig Data into a better business strategy, improving outcomes withinnovation and efficient use of technology. Examine the major emerging patterns in Big Data Consider the debate surrounding the ethical use of data Recognize patterns and improve personal and organizationalperformance Make more informed decisions with quantifiable results In an information society, it is becoming increasingly importantto make sense of data in an economically viable way. It can drivenew revenue streams and give companies a competitive advantage,providing a way forward for businesses navigating an increasinglycomplex marketplace. Big Data Revolution provides expertinsight on the tool that can revolutionize industries.
Data is everywhere. There is no way to stop, deny or avoid it. Big Data is the next economic revolution. After the triumphant success of the Internet, the capabilities of managers to use the endless and steadily increasing amount of data will split companies into those who know what they do, and those who just guess. There will only be winners or losers. Managers need to understand that we are on the verge of a new economic era. The more they listen and learn, the higher the chance to win the data race. Why is Big Data so important? Big Data can help companies to increase their revenues, improve their profit margins, reduce risks and cut costs. Intelligent use of data supports customer acquisition, allows for higher prices, minimizes the risk of unprofitable investments, improves profit margins, supports the direct distribution channels, and helps to bypass expansive third-party vendors. It also generates customer loyalty and eventually helps to reduce technology, administration and payroll costs. There are manifold reasons to take a deeper look into Big Data. In medieval times, merchants in the Mediterranean accumulated extreme wealth by trading in spices such as salt. Nowadays, the prosperity of a company strongly correlates with its ability to manage and use customer data.

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