scholarly journals Building an agile data analytics environment to support university decision‐making: A case study of Ohio State University's rapid development of a COVID‐19 dashboard system

2020 ◽  
Vol 2020 (187-188) ◽  
pp. 31-42
Author(s):  
Henry Y. Zheng ◽  
Eric Mayberry ◽  
Leanne Stanley
Keyword(s):  
Decision Making ◽  
Data Analytics ◽  
Rapid Development

Examining the potential of textual big data analytics for public policy decision-making: A case study with driverless cars in Denmark

2020 ◽  
Vol 98 ◽  
pp. 68-78 ◽  
Author(s):  
Aseem Kinra ◽  
Samaneh Beheshti-Kashi ◽  
Rasmus Buch ◽  
Thomas Alexander Sick Nielsen ◽  
Francisco Pereira
Keyword(s):  
Public Policy ◽  
Decision Making ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Policy Decision ◽  
Driverless Cars ◽  
Policy Decision Making

‘Stepping on the heads of our Gods'

2015 ◽  
Vol 6 (2) ◽  
pp. 40-56
Author(s):  
Yangji Doma Sherpa ◽  
A. John Sinclair ◽  
Thomas Henley
Keyword(s):  
Decision Making ◽  
Rapid Development ◽  
High Mountain ◽  
Court Cases ◽  
The Public ◽  
Mountain Environments ◽  
Hydroelectric Dam ◽  
Decision Making Processes

The Himalayan region of India is experiencing rapid development in tourism, agriculture, highway construction and hydroelectric dam construction. This research considered the role of the public both within and outside of development decision-making processes in these high mountain environments using the proposed Himalayan Ski Village (HSV) in Manali as a case study. The qualitative data revealed that there has been an extensive array of public participation activity related to the HSV project over approximately 10 years. Very little of this activity has evolved, however, through the formal decision-making process. Rather, most participation activities, such as general house meetings, objection letters, public rallies, court cases against the proposed project, and a religious congregation were instigated by the public to protest the proposed development. The findings also show that involvement in the participatory activities undertaken by the public and project proponent fostered instrumental and communicative learning outcomes.

scholarly journals Data Analytics in Banking and Financial Services

2019 ◽  
Vol 8 (S1) ◽  
pp. 67-69
Author(s):  
S. Palaniammal ◽  
V. S. Thangamani
Keyword(s):  
Decision Making ◽  
Developing Countries ◽  
Big Data ◽  
Financial Services ◽  
Data Analytics ◽  
Data Science ◽  
Banking Industry ◽  
Rapid Development ◽  
Banking Services ◽  
The Impact

In Journal of Banking and Finance [1] we are living in the era of the big data. The rapid development of scientific and data technology over the past decade has brought not only new and sophisticated analytical tools into Financial and Banking services, but also introduced the power of data science application in everyday strategic and operational management. Data analytics and science developments have been particularly valuable to financial organizations that heavily depend on financial information in their decision making processes. The article presents the research that focuses on the impact of the data and technology trends on decision making, particularly in Finance and Banking services. It covers an overview of the benefits associated with the decision analytics and the use of big data by financial organizations. The aim of the research is to highlight the areas of impact where the big data trends are creating disruptive changes to the way the Finance and banking industry traditionally operates. For example, we can see rapid changes to organisation structures, approach to competition and customer as well as the recognition of the importance of data analytics in strategic and tactical decision making. Investment in data analytics is no longer considered a luxury, but necessity, especially for the financial organizations in developing countries. Technology and data science are both forcing and enabling the financial and banking industry to respond to transformative demands and adapt to rapidly changing market conditions in order to survive and thrive in highly competitive global environment. Financial companies operating in developing countries must develop strong understanding of data-related trends and impacts as well as opportunities. This knowledge should not only be utilized for survival efforts, but also seen as the opportunity to engage at global level through innovation, flexibility, and early adoption of data science benefits. The paper also recommends further studies in related areas, which would provide additional value and awareness to the organizations that are considering their participation in the global data and analytical trends.

scholarly journals Data Storytelling with Dashboard: Accelerating Understanding Through Data Visualization in Financial Technology Company Case Study

Jurnal METRIS ◽  
2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Ferdian Suprata
Keyword(s):  
Decision Making ◽  
Data Visualization ◽  
Rapid Development ◽  
Data Driven ◽  
Decision Making Process ◽  
Business Practices ◽  
Context Data ◽  
The Impact ◽  
Financial Technology

In the rapid development many organisation rely on context data to support as well as to assist its decision making process. Consequently, Business Intelligence (BI), Dashboard, and Data Visualization emerged as primary tools in early 1990s as a way to help practitioners, data analyst, and data scientist to present context data into an actionable information for decision making process. However, despite its robust and powerful tools, recent study done by Kaggle’s survey in 2017 resulted that in the last five years, many companies were not able to create effective data-driven dashboard due to complex dataset, poor dashboard design, and insufficient storytelling. Hence, understanding of who is going to use dashboard, choosing which data and metrics to visualize in the right context, knowing how to convey information, driving engagement, and persuading audiences are essential in current business practices. This study is aimed to help practitioners to understand the impact of effective dashboard can have on decision making process, to design leveraging dashboard, and to present the dashboard in storytelling. A literature study is performed to gather all relevant information resulted in guidelines for dashboard creator. Case study in financial technology company is applied to experiment and to test the guidelines for assisting dashboard creator to present data-driven insight to the stakeholder.

scholarly journals Analysis of Aviation Industry for Aggressive Decision Making

2021 ◽  
pp. 625-631
Author(s):  
Mohmmed Ali Asgar Niazi ◽  
Dr. Sheikh Fahad Ahmad
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Informed Consent ◽  
General Public ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Aviation Industry ◽  
Business Objectives ◽  
Public Areas

Big Data Analytics is very useful for the business users and data scientists. It is very useful to take better, faster and right decision for the organization. Organizations and individuals should exhibit the circumspection while utilizing Big Data. In this work we intend to develop a methodology for getting ethical access of big data and ethically scrutinize it to attain the business objectives. We consider the case study of aviation sector, formulate some questions to upraise the system.  We attain the ethical permission from twitter for this purpose. We consider the tweets of general public as they were posted in public areas and falls under informed consent category.

Big Data analytics and facilities management: a case study

Facilities ◽  
2019 ◽  
Vol 38 (3/4) ◽  
pp. 268-281 ◽  
Author(s):  
Eunhwa Yang ◽  
Ipsitha Bayapu
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Data Analytics ◽  
Higher Education Institutions ◽  
Structured Interview ◽  
Software Tools ◽  
Facilities Management ◽  
Content Type ◽  
Data Elements

Purpose This paper aims to investigate data elements, transfer, gaps and the challenges to implement data analytics in facilities management. The goal is not to search for a definite solution but to gather necessary information, understand the challenges faced and develop a proper foundation for future study. Design/methodology/approach This paper used a case study approach with a qualitative method. The case of the Georgia Institute of Technology was investigated by having a semi-structured interview with six relevant personnel. The recorded interview content was analyzed and presented based on six work processes. Findings Higher education institutions are taking initiatives but facing challenges in implementing data analytics. There were 36 software tools used to manage different aspects of facilities at Georgia Tech. Identified data elements and data processing indicated that major challenges for data-driven decision-making were inconsistency in data input and structure, the issue of interoperability among different software tools and a lack of software training. Research limitations/implications The authors only interviewed individuals who work closely with data gathering, transfer and processing. Thus, the study did not explore the perspective of individuals in the leadership level or the user group level. Originality/value Facilities management departments in higher education institutions perform multi-disciplinary functions, including building automation, continuous commissioning and preventative maintenance, all of which are data- and technology-intensive. Managing this overwhelming amount of information is often a challenge, but well-planned data analytics can be used to draw keen insights about any aspect of facilities management and operations and assist in evidence-based decision-making.

A big data analytics based methodology for strategic decision making

2020 ◽  
Vol 33 (6) ◽  
pp. 1467-1490 ◽  
Author(s):  
Murat Özemre ◽  
Ozgur Kabadurmus
Keyword(s):  
Decision Making ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Market Analysis ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Strategic Decisions ◽  
Content Type ◽  
Strategic Market

PurposeThe purpose of this paper is to present a novel framework for strategic decision making using Big Data Analytics (BDA) methodology.Design/methodology/approachIn this study, two different machine learning algorithms, Random Forest (RF) and Artificial Neural Networks (ANN) are employed to forecast export volumes using an extensive amount of open trade data. The forecasted values are included in the Boston Consulting Group (BCG) Matrix to conduct strategic market analysis.FindingsThe proposed methodology is validated using a hypothetical case study of a Chinese company exporting refrigerators and freezers. The results show that the proposed methodology makes accurate trade forecasts and helps to conduct strategic market analysis effectively. Also, the RF performs better than the ANN in terms of forecast accuracy.Research limitations/implicationsThis study presents only one case study to test the proposed methodology. In future studies, the validity of the proposed method can be further generalized in different product groups and countries.Practical implicationsIn today’s highly competitive business environment, an effective strategic market analysis requires importers or exporters to make better predictions and strategic decisions. Using the proposed BDA based methodology, companies can effectively identify new business opportunities and adjust their strategic decisions accordingly.Originality/valueThis is the first study to present a holistic methodology for strategic market analysis using BDA. The proposed methodology accurately forecasts international trade volumes and facilitates the strategic decision-making process by providing future insights into global markets.

‘Stepping on the Heads of Our Gods'

2019 ◽  
pp. 236-254
Author(s):  
Yangji Doma Sherpa ◽  
A. John Sinclair ◽  
Thomas Henley
Keyword(s):  
Decision Making ◽  
Rapid Development ◽  
High Mountain ◽  
Court Cases ◽  
The Public ◽  
Mountain Environments ◽  
Hydroelectric Dam ◽  
Decision Making Processes

The Himalayan region of India is experiencing rapid development in tourism, agriculture, highway construction and hydroelectric dam construction. This research considered the role of the public both within and outside of development decision-making processes in these high mountain environments using the proposed Himalayan Ski Village (HSV) in Manali as a case study. The qualitative data revealed that there has been an extensive array of public participation activity related to the HSV project over approximately 10 years. Very little of this activity has evolved, however, through the formal decision-making process. Rather, most participation activities, such as general house meetings, objection letters, public rallies, court cases against the proposed project, and a religious congregation were instigated by the public to protest the proposed development. The findings also show that involvement in the participatory activities undertaken by the public and project proponent fostered instrumental and communicative learning outcomes.

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