Opportunities and Challenges of Big Data in Public Sector

2016 ◽  
pp. 289-301 ◽  
Author(s):  
Anil Aggarwal
Keyword(s):  
Big Data ◽  
Public Sector ◽  
Modern Society ◽  
Data Access ◽  
Weather Forecasts ◽  
Societal Benefit ◽  
Data Application ◽  
Big Data Application ◽  
Us Census

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.

Opportunities and Challenges of Big Data in Public Sector

Web Services ◽  
2019 ◽  
pp. 1749-1761 ◽  
Author(s):  
Anil K. Aggarwal
Keyword(s):  
Big Data ◽  
Public Sector ◽  
Modern Society ◽  
Data Access ◽  
Weather Forecasts ◽  
Societal Benefit ◽  
Data Application ◽  
Big Data Application ◽  
Us Census

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.

Big Data Application in Entrepreneurship

2020 ◽  
pp. 214-240
Author(s):  
León Darío Parra ◽  
Milenka Linneth Argote Cusi
Keyword(s):  
Big Data ◽  
Modern Society ◽  
Advantages And Disadvantages ◽  
The Core ◽  
Data Application ◽  
Big Data Technologies ◽  
Big Data Application ◽  
Global Entrepreneurship ◽  
Gem Data

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.

scholarly journals Big Data Analytic Framework for Organizational Leverage

2021 ◽  
Vol 11 (5) ◽  
pp. 2340
Author(s):  
Sanjay Mathrani ◽  
Xusheng Lai
Keyword(s):  
Big Data ◽  
Web Sites ◽  
Big Data Analytics ◽  
Building Blocks ◽  
Application Service ◽  
Data Application ◽  
Other Information ◽  
Big Data Application ◽  
Diverse Data ◽  
Framework System

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.

Preliminary Benefits of Big Data in the Construction Industry: A Case Study

2022 ◽  
pp. 1-11
Author(s):  
Bernard Tuffour Atuahene ◽  
Sittimont Kanjanabootra ◽  
Thayaparan Gajendran
Keyword(s):  
Big Data ◽  
Construction Industry ◽  
Construction Projects ◽  
Big Data Applications ◽  
Data Application ◽  
Construction Firm ◽  
Big Data Application ◽  
Tangible Benefit ◽  
Design Construction

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.

scholarly journals Federated Learning in Big Data Application and Sharing

2020 ◽  
Author(s):  
Jing Yang ◽  
Quan Zhang ◽  
Kunpeng Liu ◽  
Peng Jin ◽  
Guoyi Zhao
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
The State ◽  
Ideal Model ◽  
Local Data ◽  
Data Safety ◽  
Big Data Applications ◽  
Data Application ◽  
Big Data Application ◽  
Uniform Model

In recent years, electricity big data has extensive applications in the grid companies across the provinces. However, certain problems are encountered including, the inability to generate an ideal model using the isolated data possessed by each company, and the priority concerns for data privacy and safety during big data application and sharing. In this pursuit, the present research envisaged the application of federated learning to protect the local data, and to build a uniform model for different companies affiliated to the State Grid. Federated learning can serve as an essential means for realizing the grid-wide promotion of the achievements of big data applications, while ensuring the data safety.

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