Big Data and Cloud Computing for Development

Lessons from Key Industries and Economies in the Global South

Nir Kshetri,Torbjörn Fredriksson,Diana Carolina Rojas Torres

• Editore: Routledge
• Anno: 2017
• ISBN:
  9781134973446
• Edizione: 1
• Argomento: Economia
• Categoria: Economia dello sviluppo

This book provides a framework for evaluating big data and cloud computing based on how they evolve to fit users' needs in developing countries in key areas, such as agriculture and education. The authors discuss how this framework can be utilized by businesses, governments, and consumers to accelerate economic growth and overcome information and communication barriers.

By examining the ways in which cloud computing can drive social, economic, and environmental transformation, readers gain a nuanced understanding of the opportunities and challenges these technologies offer. The authors also provide an authoritative and up-to-date account of big data's diffusion into a wide range of developing economies, such as Brazil and China, illustrating key concepts through in-depth case studies. Special attention is paid to economic development in the context of the new Sustainable Development Goals formulated by the United Nations, introducing readers to the most modern standard of economic evaluation.

Students of information management, entrepreneurship, and development, as well as policy makers, researchers, and practitioners, will find Big Data and Cloud Computing for Development an interesting read and a useful reference source.

PART III
Case Studies of Diffusion and Impact of BD and Cloud Computing in Major Economies in the Global South

7
SUB-SAHARAN AFRICA

7.1 Introduction

BD and the cloud have become increasingly pervasive in SSA economies. According to the undersea cable operator, MainOne, the African cloud market was US$35.6 billion in 2015.¹ The market research company, IDC estimated that South African cloud services market reached US$230 million in 2014.²

According to IBM, as of 2014, about half of the medium and large businesses in South Africa and Kenya had adopted the cloud.³ A survey of World Wide Worx and Cisco revealed that 44 percent of Nigerian businesses had plans to adopt the cloud in 2014. Another study found that at least 40 percent of businesses in Nigeria and Kenya were in the planning stages of BD projects in 2015.⁴

Some economic sectors are more advanced than others in the adoption of BD analytics and the cloud. For instance, SSA-based firms in retail, telecoms, oil and gas, and banking are most likely to use the cloud to handle large volumes of data transactions.⁵ To take an example, in Nigeria and Angola, the oil industry has driven the investment in data centers. This industry exhibits a high degree of orientation towards the global market.⁶

Most SSA economies in the past needed to rely on satellite for Internet connection. Satellite-based connections are expensive. Moreover signals often need to take a 76,000 km round-trip to and from orbits. The resulting delays are especially disruptive and troubling for data-intensive applications or banking transactions.⁷ In this regard, an important factor is that undersea cables have landed in some of these economies. Due to this, data centers are growing rapidly in Kenya and other countries.⁸

Competitively priced fast and ultra-fast internet access is becoming widely available in SSA economies. The region’s telecom companies are using this as a selling point to attract customers. For instance, Liquid’s ads in Zambia and Zimbabwe say that it takes a shorter time to download a movie than to prepare popcorn by microwave.⁹

Major challenges and barriers to the BD and the cloud pathways include the lack of local infrastructures, unaffordability, and relatively narrow local offerings. For instance, according to Seacom, in 2014, 90 percent of African internet content was hosted outside the continent. The resulting latency has a visible effect on video streaming and other bandwidth consuming applications. Such services and applications also cost more on the continent.¹⁰

7.2 The Current State of BD and Cloud Market

A number of creative BD- and cloud-based apps have been developed that are unique to SSA economies.

7.2.1 Education

The Higher Education Alliance for Leadership through Health, a consortium of seven universities (in Kenya, Ethiopia, the Democratic Republic of Congo, Tanzania, and Uganda), works with industry experts to extend education through virtual labs that students access remotely.

South Africa’s Center for Higher Education Transformation lets African universities access and manipulate its performance data stored on a Google platform.¹¹ Also, Google has provided its cloud-based Apps for Education to universities in Rwanda, Kenya, and Mauritius.

In 2009, Microsoft donated 250,000 laptops to teachers in Ethiopia. The software in the laptop is managed by the US company FullArmor through Microsoft’s Azure cloud platform.¹² Teachers can download curriculum; maintain, view, and track academic records; and transfer student data securely.¹³

7.2.2 Health Care

As explained in Chapter 1, in South Africa, the Mothers-2-Mothers (M2M) program combines the cloud with database technology and mobile services to fight HIV/AIDS transmission from mother to children. M2M digitizes patient records and shares them with counselors across its networks of over 700 sites in Africa. The records contain information on treatment plans and advanced reporting tools, which allow quick response. As of 2011, M2M had served more than 1.5 million women in nine Sub-Saharan African countries.

In Nigeria and Ghana, a cloud-based app is used to identify fake prescription drugs. When buying a drug, a customer can find a twelve-digit code by scratching a sticker on the package and can then send a text message to a number. The code is matched with that registered by the pharmaceutical company in HP’s cloud database. The customer receives a response back that tells whether the drug is counterfeit.

Scientists hope that it is possible to use BD to dramatically reduce and even eliminate some diseases such as malaria. For instance, in Namibia, satellite imagery is being used to map environmental conditions that can help malaria parasites and mosquitos to grow. For instance, factors such as vegetation density, population, and rainfall which are found to affect mosquito and parasite populations and the rate of transmission are tracked. This information is combined with the movement pattern of malaria-infected people. Anonymized cellphone records of over two million users provided by Namibia’s largest network provider, Mobile Telecommunications Limited (MTC), was used to study travel patterns. This information allowed interventions such as indoor spraying with insecticide to disrupt the malaria transmission cycle. For instance, in 2013, Namibia’s Ministry of Health used the information to target bed net distribution and indoor insecticide spraying to areas with urgent needs. The limited resources were used to reach 80,000 people that were most likely to be affected by the malaria transmission cycle.¹⁴

7.2.3 Farming and Agriculture

Improving agricultural productivity is likely to be among the most positive effects of BD in SSA economies. It is estimated that the average African smallholder farmer produces only a quarter to half of the productive potential. BD can help them make full use of their productive potential. BD can also help farmers reduce costs by providing access to detailed information about irrigation and reduce wastage in resources.¹⁵

A number of efforts and initiatives are being undertaken to digitize SSA’s agricultural activities. A promising area of BD and cloud utilization to increase agriculture productivity is soil infrared spectroscopy. Data about soil characteristics such as texture, organic matter, and fertility help determine fertilizer needs and can be used as a basis for precise prescriptions. One way to get information about soil characteristics is to use orbiting satellites, which can collect data in a cost-effective manner by measuring electromagnetic radiation reflected from farmlands.¹⁶ Efforts have been made to develop national and regional databases for soil properties. In 2009, Nairobi, Kenya-based World Agroforestry Centre started cataloguing the radiation signature of about 100,000 samples of African soils. It also announced a plan to give the information to Colombia-based International Centre for Tropical Agriculture in order to build a database, known as the Digital Soil Map. The goal of the project was to combine the information with regularly updated satellite imagery of farmland in forty-two Af...

Indice dei contenuti

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• List of Figures
• List of Tables
• Preface and Acknowledgments
• List of Abbreviations
• Part I Big Data and Cloud Computing in the Global South: Key Concepts, Issues, Opportunities, and Challenges
• Part II Big Data and Cloud Computing in Key Development Areas in the Global South
• Part III Case Studies of Diffusion and Impact of BD and Cloud Computing in Major Economies in the Global South
• Part IV Lessons Learned, Implications, and the Way Forward
• Index