Big Data Application in Entrepreneurship

Author(s):  
León Darío Parra ◽  
Milenka Linneth Argote Cusi

Modern society generates about 7 Zetabytes each year, of which 75% comes from the connectivity of individuals to social networks. In this regard, the chapter presents a case study of the application of big data technologies for entrepreneurial analysis using global entrepreneurship monitor (GEM) data as a new tool of analysis. Therefore, the core of this chapter is to present the methodology that was used to develop and implement the big data app of GEM as well as the main results of project. On the other hand, the chapter remarks the advantages and disadvantages of this kind of technology for the case of GEM data. Finally, it presents the respective dashboards that interrelate the gem data with Word Bank indicators as a case study of the application of big data for entrepreneurship research.

Author(s):  
Bernard Tuffour Atuahene ◽  
Sittimont Kanjanabootra ◽  
Thayaparan Gajendran

Big data applications consist of i) data collection using big data sources, ii) storing and processing the data, and iii) analysing data to gain insights for creating organisational benefit. The influx of digital technologies and digitization in the construction process includes big data as one newly emerging digital technology adopted in the construction industry. Big data application is in a nascent stage in construction, and there is a need to understand the tangible benefit(s) that big data can offer the construction industry. This study explores the benefits of big data in the construction industry. Using a qualitative case study design, construction professionals in an Australian Construction firm were interviewed. The research highlights that the benefits of big data include reduction of litigation amongst projects stakeholders, enablement of near to real-time communication, and facilitation of effective subcontractor selection. By implication, on a broader scale, these benefits can improve contract management, procurement, and management of construction projects. This study contributes to an ongoing discourse on big data application, and more generally, digitization in the construction industry.


Author(s):  
Anil Aggarwal

Data has always been the backbone of modern society. It is generated by individuals, businesses and governments. It is used in many citizen-centric applications, including weather forecasts, controlling diseases, monitoring undesirables etc. What is changing is the source of data. Advances in technology are allowing data to be generated from any devise at any place in any form. The challenge is to “understand”, “manage” and make use of this data. It is well known that government generates unprecedented amount of data (ex: US census), the question remains: can this data be combined with technology generated data to make it useful for societal benefit. Governments and non-profits, however, work across borders making data access and integration challenging. Rules, customs and politics must be followed while sharing data across borders. Despite these challenges, big data application in public sector are beginning to emerge. This chapter discusses areas of government applications and also discusses challenges of developing such systems.


This exploratory study aims to assess and investigate Brunei Darussalam’s readiness in developing and applying big data technologies for its public and private sectors, using Social, Technological, Environmental and Policy (STEP) framework. The results show that the population are digitally literate (Social) and utilises smart devices as well as internet network connectivity that is widely offered by the local telecommunications company (Technology). The government of Brunei Darussalam established multiple digital transformation initiatives including implementation of 5G connectivity as well as digital economy masterplan to digitally transformed in the near future (Environment). Regardless of the absence of national digital data privacy policy (Policy) in Brunei, the recent nation’s successful big data application in public sector – BruHealth Application – to contain Covid-19 community spread was achieved. Alas, the existence of such policy in the near future will create opportunities for the local private sectors to capitalise big data technologies to their business strategies.


2021 ◽  
Vol 9 (2) ◽  
pp. 370-375
Author(s):  
Divya Dangi, Et. al.

The data volume increases every day and the next wave of apps cannot be envisaged without the created and executed data-driven algorithms. In this post, we undertook an extensive survey on privacy issues in the context of big data. At every point of the Big Data life cycle, we explored privacy challenges and discussed some of the advantages and disadvantages of the Big Data application of new privacy conservation schemes. Much progress has been made in protecting the protection of consumers from data production to data storage, but many transparent questions and hurdles exist.


Web Services ◽  
2019 ◽  
pp. 1749-1761 ◽  
Author(s):  
Anil K. Aggarwal

Data has always been the backbone of modern society. It is generated by individuals, businesses and governments. It is used in many citizen-centric applications, including weather forecasts, controlling diseases, monitoring undesirables etc. What is changing is the source of data. Advances in technology are allowing data to be generated from any devise at any place in any form. The challenge is to “understand”, “manage” and make use of this data. It is well known that government generates unprecedented amount of data (ex: US census), the question remains: can this data be combined with technology generated data to make it useful for societal benefit. Governments and non-profits, however, work across borders making data access and integration challenging. Rules, customs and politics must be followed while sharing data across borders. Despite these challenges, big data application in public sector are beginning to emerge. This chapter discusses areas of government applications and also discusses challenges of developing such systems.


Author(s):  
Muhammad Azmi Sait ◽  
Muhammad Anshari Ali

This exploratory study aims to assess and investigate Brunei Darussalam’s readiness in developing and applying big data technologies for its public and private sectors, using Social, Technological, Environmental and Policy (STEP) framework. The results show that the population are digitally literate (Social) and utilises smart devices as well as internet network connectivity that is widely offered by the local telecommunications company (Technology). The government of Brunei Darussalam established multiple digital transformation initiatives including implementation of 5G connectivity as well as digital economy masterplan to digitally transformed in the near future (Environment). Regardless of the absence of national digital data privacy policy (Policy) in Brunei, the recent nation’s successful big data application in public sector – BruHealth Application – to contain Covid-19 community spread was achieved. Alas, the existence of such policy in the near future will create opportunities for the local private sectors to capitalise big data technologies to their business strategies.


2021 ◽  
Vol 11 (5) ◽  
pp. 2340
Author(s):  
Sanjay Mathrani ◽  
Xusheng Lai

Web data have grown exponentially to reach zettabyte scales. Mountains of data come from several online applications, such as e-commerce, social media, web and sensor-based devices, business web sites, and other information types posted by users. Big data analytics (BDA) can help to derive new insights from this huge and fast-growing data source. The core advantage of BDA technology is in its ability to mine these data and provide information on underlying trends. BDA, however, faces innate difficulty in optimizing the process and capabilities that require merging of diverse data assets to generate viable information. This paper explores the BDA process and capabilities in leveraging data via three case studies who are prime users of BDA tools. Findings emphasize four key components of the BDA process framework: system coordination, data sourcing, big data application service, and end users. Further building blocks are data security, privacy, and management that represent services for providing functionality to the four components of the BDA process across information and technology value chains.


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