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It presents a case study of big data innovations in Stelcorp? a state electricity corporation in India. In an attempt to address losses in electricity distribution, Stelcorp has introduced new digital meters throughout the distribution network to capture big data, and organisation-wide information systems that store and process and disseminate big data. Emergent issues are identified across three domains: implementation, value and outcome. Implementation of big data has worked relatively well but technical and human challenges remain. The advent of big data has enabled some ?albeit constrained ?value addition in all areas of organisational operation: customer billing, fault and loss detection, performance measurement, and planning. Yet US$ tens of millions of investment in big data has brought no aggregate improvement in distribution losses or revenue collection. This can be explained by the wider outcome, with big data faltering in the face of external politics; in this case the electoral politics of electrification. Alongside this reproduction of power, the paper also reflects on the way in which big data has enabled shifts in the locus of power: from public to private sector; from labour to management; and from lower to higher levels of management. A number of conceptual frameworks emerge as having analytical power in studying big data and global development. The information value chain model helps track both implementation and value-creation of big data projects. The design-reality gap model can be used to analyse the nature and extent of barriers facing big data projects in developing countries. And models of power ?resource dependency, epistemic models, and wider frameworks ?are all shown as helping understand the politics of big data. 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window.loswp.work = {"work":{"id":31268528,"created_at":"2017-02-06T21:37:35.386-08:00","from_world_paper_id":null,"updated_at":"2021-01-17T21:12:52.777-08:00","_data":{"abstract":"This paper presents exploratory research into data-intensive development that seeks to inductively identify issues and conceptual frameworks of relevance to big data in developing countries. It presents a case study of big data innovations in Stelcorp? a state electricity corporation in India. In an attempt to address losses in electricity distribution, Stelcorp has introduced new digital meters throughout the distribution network to capture big data, and organisation-wide information systems that store and process and disseminate big data. Emergent issues are identified across three domains: implementation, value and outcome. Implementation of big data has worked relatively well but technical and human challenges remain. The advent of big data has enabled some ?albeit constrained ?value addition in all areas of organisational operation: customer billing, fault and loss detection, performance measurement, and planning. Yet US$ tens of millions of investment in big data has brought no aggregate improvement in distribution losses or revenue collection. This can be explained by the wider outcome, with big data faltering in the face of external politics; in this case the electoral politics of electrification. Alongside this reproduction of power, the paper also reflects on the way in which big data has enabled shifts in the locus of power: from public to private sector; from labour to management; and from lower to higher levels of management. A number of conceptual frameworks emerge as having analytical power in studying big data and global development. The information value chain model helps track both implementation and value-creation of big data projects. The design-reality gap model can be used to analyse the nature and extent of barriers facing big data projects in developing countries. And models of power ?resource dependency, epistemic models, and wider frameworks ?are all shown as helping understand the politics of big data.\n\nA more detailed version of the paper also came out as a working paper in Development Informatics at the University of Manchester, a copy from which is uploaded here"},"document_type":"other","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"Exploring big data for development: an electricity sector case study from India","broadcastable":true,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [481982]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "full_page_mobile_sutd_modal"; window.loswp.useOptimizedScribd4genScript = false; window.loginModal = {}; window.loginModal.appleClientId = 'edu.academia.applesignon';</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{"location":"swp-splash-paper-cover","attachmentId":52464485,"attachmentType":"pdf"}"><img alt="First page of “Exploring big data for development: an electricity sector case study from India”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/52464485/mini_magick20190122-29949-m7tyi1.png?1548223554" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/images/single_work_splash/adobe_icon.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">Exploring big data for development: an electricity sector case study from India</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="481982" href="https://jgu.academia.edu/RitamSengupta"><img alt="Profile image of Ritam Sengupta" class="ds-work-card--author-avatar" src="https://0.academia-photos.com/481982/162970/152163589/s65_ritam.sengupta.jpg" />Ritam Sengupta</a></div><div class="ds-work-card--detail"><div class="ds-work-card--work-metadata"><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">visibility</span><p class="ds2-5-body-sm" id="work-metadata-view-count">…</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">description</span><p class="ds2-5-body-sm">32 pages</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">link</span><p class="ds2-5-body-sm">1 file</p></div></div><script>(async () => { const workId = 31268528; 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if (!viewCountBody) { throw new Error('Failed to find work views element'); } viewCountBody.textContent = `${commaizedViewCount} views`; } catch (error) { // Remove the whole views element if there was some issue parsing. document.getElementById('work-metadata-view-count')?.parentNode?.remove(); throw new Error(`Failed to parse view count: ${viewCount}`, error); } }; // If the DOM is still loading, wait for it to be ready before updating the view count. if (document.readyState === "loading") { document.addEventListener('DOMContentLoaded', () => { updateViewCount(viewCount); }); // Otherwise, just update it immediately. } else { updateViewCount(viewCount); } })();</script></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">This paper presents exploratory research into data-intensive development that seeks to inductively identify issues and conceptual frameworks of relevance to big data in developing countries. It presents a case study of big data innovations in Stelcorp? a state electricity corporation in India. In an attempt to address losses in electricity distribution, Stelcorp has introduced new digital meters throughout the distribution network to capture big data, and organisation-wide information systems that store and process and disseminate big data. Emergent issues are identified across three domains: implementation, value and outcome. Implementation of big data has worked relatively well but technical and human challenges remain. The advent of big data has enabled some ?albeit constrained ?value addition in all areas of organisational operation: customer billing, fault and loss detection, performance measurement, and planning. Yet US$ tens of millions of investment in big data has brought no aggregate improvement in distribution losses or revenue collection. This can be explained by the wider outcome, with big data faltering in the face of external politics; in this case the electoral politics of electrification. Alongside this reproduction of power, the paper also reflects on the way in which big data has enabled shifts in the locus of power: from public to private sector; from labour to management; and from lower to higher levels of management. A number of conceptual frameworks emerge as having analytical power in studying big data and global development. The information value chain model helps track both implementation and value-creation of big data projects. The design-reality gap model can be used to analyse the nature and extent of barriers facing big data projects in developing countries. And models of power ?resource dependency, epistemic models, and wider frameworks ?are all shown as helping understand the politics of big data. A more detailed version of the paper also came out as a working paper in Development Informatics at the University of Manchester, a copy from which is uploaded here</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":52464485,"attachmentType":"pdf","workUrl":"https://www.academia.edu/31268528/Exploring_big_data_for_development_an_electricity_sector_case_study_from_India"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":52464485,"attachmentType":"pdf","workUrl":"https://www.academia.edu/31268528/Exploring_big_data_for_development_an_electricity_sector_case_study_from_India"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div></div><div data-auto_select="false" data-client_id="331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b" data-doc_id="52464485" data-landing_url="https://www.academia.edu/31268528/Exploring_big_data_for_development_an_electricity_sector_case_study_from_India" data-login_uri="https://www.academia.edu/registrations/google_one_tap" data-moment_callback="onGoogleOneTapEvent" id="g_id_onload"></div><div class="ds-top-related-works--grid-container"><div class="ds-related-content--container ds-top-related-works--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="0" data-entity-id="6275763" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/6275763/The_Politics_of_Big_Data_A_Three_Level_Analysis">The Politics of Big Data: A Three-Level Analysis</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="961645" href="https://huji.academia.edu/APeled">Alon Peled</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2013</p><p class="ds-related-work--abstract ds2-5-body-sm">What role does politics play in the emerging Big Data domain? The paper argues that Big Data political power struggles surface at three distinct levels of analysis: the social sciences, the information state, and bureaucratic politics. At the social sciences level of analysis, Big Data threatens to divide social scientists into antagonistic methodological camps as it does not conform to traditional research techniques. At the information state level of analysis, a handful of powerful agencies and corporations created around data generation are consolidating their competitive advantage and are unlikely to support important data access and privacy protections. The one brighter spot for Big Data is found inside governmental bureaucracy. Here, trends such as “governance by numbers” at the sub-national level and mutually profitable data exchanges at the national level suggest that Big Data may propel agencies to share information better. The article concludes with a proposal to view Dr. John Snow and his work to stop the cholera epidemic in central London in 1854 as an early harbinger of the Big Data movement. Snow’s work displays redeeming features that may mitigate less desirable effects of Big Data projects across the three levels of analysis. These features are a sense of purpose, ingenuity, clever data collection design, collaboration, humility and humanity. Lay summary: The paper explores the role of political power struggles in the emergent big data domain. It finds that power struggles manifest in three arenas: the social sciences, the information state, and public sector bureaucracy. The most positive opportunities for utilizing and advancing big data are in the arena of government bureaucracy where big data may prompt agencies to engage in more efficient data sharing. Publication significance: Big data and its impact on the citizen, society and the state is of increasing importance in the information state. This timely paper examines the political power struggles that influence the potential of big data to benefit or burden citizens and the state. The paper's findings (that big data is potentially most beneficial at the level of government bureaucracy where it can prompt agencies to share data more efficiently) present a focused future direction for big data research and innovation.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"The Politics of Big Data: A Three-Level Analysis","attachmentId":33126218,"attachmentType":"pdf","work_url":"https://www.academia.edu/6275763/The_Politics_of_Big_Data_A_Three_Level_Analysis","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/6275763/The_Politics_of_Big_Data_A_Three_Level_Analysis"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="48589831" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/48589831/Big_Data_Issues_for_an_International_Political_Sociology_of_Data_Practices_Table_1">Big Data: Issues for an International Political Sociology of Data Practices: Table 1</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="110705643" href="https://independent.academia.edu/MFlyverbom">Mikkel Flyverbom</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Political Sociology, 2016</p><p class="ds-related-work--abstract ds2-5-body-sm">The claim that big data can revolutionize strategy and governance in the context of international relations is increasingly hard to ignore. Scholars of international political sociology have mainly discussed this development through the themes of security and surveillance. The aim of this paper is to outline a research agenda that can be used to raise a broader set of sociological and practice-oriented questions about the increasing datafication of international relations and politics. First, it proposes a way of conceptualizing big data that is broad enough to open fruitful investigations into the emerging use of big data in these contexts. This conceptualization includes the identification of three moments contained in any big data practice. Secondly, it suggests a research agenda built around a set of sub-themes that each deserve dedicated scrutiny when studying the interplay between big data and international relations along these moments. Through a combination of these moments and sub-themes, the paper suggests a roadmap for an international political sociology of the datafication of worlds.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Big Data: Issues for an International Political Sociology of Data Practices: Table 1","attachmentId":67123039,"attachmentType":"pdf","work_url":"https://www.academia.edu/48589831/Big_Data_Issues_for_an_International_Political_Sociology_of_Data_Practices_Table_1","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/48589831/Big_Data_Issues_for_an_International_Political_Sociology_of_Data_Practices_Table_1"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="37186638" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/37186638/Policy_Visions_of_Big_Data_Views_from_the_Global_South">Policy Visions of Big Data: Views from the Global South</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="27044075" href="https://tum-de.academia.edu/LauraMahrenbach">Laura C Mahrenbach</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="903942" href="https://univie.academia.edu/KatjaMayer">Katja Mayer</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Third World Quarterly, 2018</p><p class="ds-related-work--abstract ds2-5-body-sm">Government intentions stand at the heart of debates about how big data can and should be used in the Global South. This paper provides new insights by examining the political and economic visions promoted by emerging power governments in Brazil, India and China (the BICs). Doing so is crucial as these countries not only comprise some of the world’s largest populations, but have also demonstrated their initiative in national and international promotion of big data politics. Drawing on a content analysis of strategic and legal documents discussing the use of big data, we identify potential areas for big data cooperation among the BICs by determining the compatibility of national policy visions. Three visions are apparent: data as a force for political liberation or repression, for improving public services and for facilitating development. Successful BIC cooperation is likely related to the latter two, but less probable for the liberation/repression vision. We conclude by identifying the implications of BIC engagement with big data for the Global South more broadly. SEE HERE: https://www.tandfonline.com/doi/full/10.1080/01436597.2018.1509700</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Policy Visions of Big Data: Views from the Global South","attachmentId":57720269,"attachmentType":"pdf","work_url":"https://www.academia.edu/37186638/Policy_Visions_of_Big_Data_Views_from_the_Global_South","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/37186638/Policy_Visions_of_Big_Data_Views_from_the_Global_South"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="30760972" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/30760972/Introduction_Politics_of_Big_Data_Special_Issue_Digital_Culture_and_Society_2_2_2016">Introduction: Politics of Big Data Special Issue, Digital Culture & Society 2:2, 2016</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="553103" href="https://kcl.academia.edu/JenniferPybus">Jennifer Pybus</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="1261401" href="https://ucm.academia.edu/PaoloGerbaudo">Paolo Gerbaudo</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="344977" href="https://kcl.academia.edu/MarkCot%C3%A9">Mark Coté</a></div><p class="ds-related-work--abstract ds2-5-body-sm">This special issue oﬀers a critical dialogue around the myriad political dimen-sions of Big Data. We begin by recognising that the technological objects of Big Data are unprecedented in the speed, scope and scale of their computation and knowledge production. This critical dialogue is grounded in an equal recogni-tion of continuities around Big Data’s social, cultural, and political economic dimensions. Big Data, then, is political in the same way in which identity, the body, gender, sexuality, race and ethnicity are political, that is, as sites of struggle over meaning, interpretations, and categorisations of lived experience. Big Data is political in the way circuits of production, distribution, and consumption are political; that is, as sites where access, control and agency are unequally distrib-uted through asymmetrical power relations, including relations of data produc-tion. Big Data is political in the way contemporary politics are being reshaped by data analysis in electoral campaign strategy, and through state surveillance as strikingly evidenced by the Snowden revelations on the NSA and GCHQ. Big Data is also political in the contestation of this advanced scientiﬁc practice, wherein the generation of data at unprecedented scale promises a precise and objective measure of everyday life. However, the computational dreams of an N = all verisimilitude – that is, of datasets providing a one-to-one correspon-dence to a given phenomenon – are haunted by the normative biases embedded in all data. This is not to suggest that Big Data – more speciﬁcally processes of dataﬁcation1 – are best or at all understood as socially constructed. Indeed, discursive analysis or unreconstructed social theory cannot fully grasp how data re-articulates the social, cultural, political and economic in a deeply recursive manner. Thus, any political reckoning must equally account for the materiality of data, alongside the logic guiding its processes and the practices that deploy its tools. In short, what are the power relations animating the knowledge generated by data analytics?</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Introduction: Politics of Big Data Special Issue, Digital Culture \u0026 Society 2:2, 2016","attachmentId":51198450,"attachmentType":"pdf","work_url":"https://www.academia.edu/30760972/Introduction_Politics_of_Big_Data_Special_Issue_Digital_Culture_and_Society_2_2_2016","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/30760972/Introduction_Politics_of_Big_Data_Special_Issue_Digital_Culture_and_Society_2_2_2016"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="56135468" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/56135468/Introduction_Politics_of_Big_Data">Introduction. Politics of Big Data</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="344977" href="https://kcl.academia.edu/MarkCot%C3%A9">Mark Coté</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Digital Culture & Society, 2016</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Introduction. Politics of Big Data","attachmentId":71670675,"attachmentType":"pdf","work_url":"https://www.academia.edu/56135468/Introduction_Politics_of_Big_Data","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/56135468/Introduction_Politics_of_Big_Data"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="44428110" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/44428110/Left_to_Other_Peoples_Devices_A_Political_Economy_Perspective_on_the_Big_Data_Revolution_in_Development">Left to Other Peoples' Devices? A Political Economy Perspective on the Big Data Revolution in Development</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="14715680" href="https://lse.academia.edu/LauraMann">Laura Mann</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Development and Change, 2018</p><p class="ds-related-work--abstract ds2-5-body-sm">This article brings a political economy perspective to the field of Data for Development (D4D). It highlights the fact that many projects involve extracting data from African-based organizations for expert analysis in advanced economies. This extraction is justified on the basis that it is being used for humanitarian purposes. Key actors including the UN Global Pulse and World Economic Forum have lobbied for a governance framework emphasizing greater emission, personalization and centralization of data. The article shows how this approach enables the strategies of multinational corporations which are aiming to become data custodians of Africa's emerging economies. Little attention has been paid to the geographical distribution of capacity building nor to the ways in which data-driven restructuring may alter existing livelihoods. As African economies become increasingly 'digital', data will become a source of power in economic governance. Current frameworks amount to a kind of industrial policy that supports the learning and innovation of foreign firms. The article aims to move D4D away from the focus on humanitarianism towards economic development, considering the opportunities for African citizens to benefit from their data as a source of revenue, knowledge and power. The conclusion suggests lines of inquiry for taking research further. 2</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Left to Other Peoples' Devices? A Political Economy Perspective on the Big Data Revolution in Development","attachmentId":64844847,"attachmentType":"pdf","work_url":"https://www.academia.edu/44428110/Left_to_Other_Peoples_Devices_A_Political_Economy_Perspective_on_the_Big_Data_Revolution_in_Development","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/44428110/Left_to_Other_Peoples_Devices_A_Political_Economy_Perspective_on_the_Big_Data_Revolution_in_Development"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="34410921" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/34410921/Critical_analysis_of_UN_latest_report_on_Big_Data_Improving_data_is_a_development_agenda_in_its_own_right_and_can_improve_the_targeting_of_existing_resources_and_spur_new_economic_opportunities_">Critical analysis of UN latest report on Big Data: “Improving data is a development agenda in its own right, and can improve the targeting of existing resources and spur new economic opportunities.”</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="30496018" href="https://oxford.academia.edu/DrShimaBeigi">Dr. Shima Beigi</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Critical analysis of UN latest report on Big Data: “Improving data is a development agenda in its own right, and can improve the targeting of existing resources and spur new economic opportunities.”","attachmentId":54291081,"attachmentType":"pdf","work_url":"https://www.academia.edu/34410921/Critical_analysis_of_UN_latest_report_on_Big_Data_Improving_data_is_a_development_agenda_in_its_own_right_and_can_improve_the_targeting_of_existing_resources_and_spur_new_economic_opportunities_","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/34410921/Critical_analysis_of_UN_latest_report_on_Big_Data_Improving_data_is_a_development_agenda_in_its_own_right_and_can_improve_the_targeting_of_existing_resources_and_spur_new_economic_opportunities_"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="10249755" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/10249755/Critiquing_Big_Data_Politics_Ethics_Epistemology_Special_Section_Introduction_">Critiquing Big Data: Politics, Ethics, Epistemology (Special Section Introduction)</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="346666" href="https://usc.academia.edu/KateMiltner">Kate M . Miltner</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="35648183" href="https://independent.academia.edu/MaryGray4">Mary Gray</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Critiquing Big Data: Politics, Ethics, Epistemology (Special Section Introduction)","attachmentId":36339126,"attachmentType":"pdf","work_url":"https://www.academia.edu/10249755/Critiquing_Big_Data_Politics_Ethics_Epistemology_Special_Section_Introduction_","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/10249755/Critiquing_Big_Data_Politics_Ethics_Epistemology_Special_Section_Introduction_"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="82674206" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/82674206/REVIEW_of_The_Trouble_With_Big_Data_by_Jennifer_Edmond_Nicola_Horsley_Jo_rg_Lehmann_and_Mike_Priddy_The_Sociological_Review">REVIEW of "The Trouble With Big Data" by Jennifer Edmond, Nicola Horsley, Jörg Lehmann and Mike Priddy - The Sociological Review</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="2229196" href="https://flame.academia.edu/TannisthaSamanta">Tannistha Samanta</a></div><p class="ds-related-work--metadata ds2-5-body-xs">The Sociological Review, 2022</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"REVIEW of \"The Trouble With Big Data\" by Jennifer Edmond, Nicola Horsley, Jörg Lehmann and Mike Priddy - The Sociological Review","attachmentId":88303370,"attachmentType":"pdf","work_url":"https://www.academia.edu/82674206/REVIEW_of_The_Trouble_With_Big_Data_by_Jennifer_Edmond_Nicola_Horsley_Jo_rg_Lehmann_and_Mike_Priddy_The_Sociological_Review","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/82674206/REVIEW_of_The_Trouble_With_Big_Data_by_Jennifer_Edmond_Nicola_Horsley_Jo_rg_Lehmann_and_Mike_Priddy_The_Sociological_Review"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="23288606" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/23288606/The_Bottom_of_the_Data_Pyramid_Big_Data_and_the_Global_South">The Bottom of the Data Pyramid: Big Data and the Global South</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="278205" href="https://independent.academia.edu/ProfdrPayalArora">Payal Arora</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Communication, 2016</p><p class="ds-related-work--abstract ds2-5-body-sm">To date, little attention has been given to the impact of big data in the Global South, about 60% of whose residents are below the poverty line. Big data manifests in novel and unprecedented ways in these neglected contexts. For instance, India has created biometric national identities for her 1.2 billion people, linking them to welfare schemes, and social entrepreneurial initiatives like the Ushahidi project that leveraged crowdsourcing to provide real-time crisis maps for humanitarian relief. While these projects are indeed inspirational, this article argues that in the context of the Global South there is a bias in the framing of big data as an instrument of empowerment. Here, the poor, or the " bottom of the pyramid " populace are the new consumer base, agents of social change instead of passive beneficiaries. This neoliberal outlook of big data facilitating inclusive capitalism for the common good sidelines critical perspectives urgently needed if we are to channel big data as a positive social force in emerging economies. This article proposes to assess these new technological developments through the lens of databased democracies, databased identities, and databased geographies to make evident normative assumptions and perspectives in this under-examined context.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"The Bottom of the Data Pyramid: Big Data and the Global South","attachmentId":43755629,"attachmentType":"pdf","work_url":"https://www.academia.edu/23288606/The_Bottom_of_the_Data_Pyramid_Big_Data_and_the_Global_South","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/23288606/The_Bottom_of_the_Data_Pyramid_Big_Data_and_the_Global_South"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":52464485,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":52464485,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_52464485" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. 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