Business Commons^™

Big Data And Analytics In The Modern Audit Engagement: Research Needs, Deniz Appelbaum, Alexander Kogan, Miklos A. Vasarhelyi

Department of Accounting and Finance Faculty Scholarship and Creative Works

Modern audit engagements often involve examination of clients that are using Big Data and analytics to remain competitive and relevant in today’s business environment. Client systems now are integrated with the cloud, the Internet of Things, and external data sources such as social media. Furthermore, many engagement clients are now integrating this Big Data with new and complex business analytical approaches to generate intelligence for decision making. This scenario provides almost limitless opportunities and the urgency for the external auditor to utilize advanced analytics. This paper first positions the need for the external audit profession to move toward Big Data …

Vungle Inc. Improves Monetization Using Big-Data Analytics, Bert De Reyck, Ioannis Fragkos, Yael Gruksha-Cockayne, Casey Lichtendahl, Hammond Guerin, Andre Kritzer

Research Collection Lee Kong Chian School Of Business

The advent of big data has created opportunities for firms to customize their products and services to unprecedented levels of granularity. Using big data to personalize an offering in real time, however, remains a major challenge. In the mobile advertising industry, once a customer enters the network, an ad-serving decision must be made in a matter of milliseconds. In this work, we describe the design and implementation of an ad-serving algorithm that incorporates machine-learning methods to make personalized ad-serving decisions within milliseconds. We developed this algorithm for Vungle Inc., one of the largest global mobile ad networks. Our approach also …

A Big Data Analytics Method For Tourist Behaviour Analysis, Shah Jahan Miah, Huy Quan Vu, John Gammack, Michael Mcgrath

All Works

© 2016 Elsevier B.V. Big data generated across social media sites have created numerous opportunities for bringing more insights to decision-makers. Few studies on big data analytics, however, have demonstrated the support for strategic decision-making. Moreover, a formal method for analysing social media-generated big data for decision support is yet to be developed, particularly in the tourism sector. Using a design science research approach, this study aims to design and evaluate a ‘big data analytics’ method to support strategic decision-making in tourism destination management. Using geotagged photos uploaded by tourists to the photo-sharing social media site, Flickr, the applicability of …

Comparative Analysis Of Big Data Analytics Software In Assessing Sample Data, Soly Mathew Biju, Alex Mathew

Journal of International Technology and Information Management

Over the last few years, big data has emerged as an important topic of discussion in most firms owing to its ability of creation, storage and processing of content at a reasonable price. Big data consists of advanced tools and techniques to process large volumes of data in organisations. Investment in big data analytics has almost become a necessity in large-sized firms, particularly multinational companies, for its unique benefits, particularly in prediction and identification of various trends. Some of the most popular big data analytics software used today are MapReduce, Hive, Tableau and Hive, while the framework Hadoop enables easy …

The Cloud, The Crowd, And The City: How New Data Practices Reconfigure Urban Governance?, Philip Ashton, Rachel Weber, Matthew Zook

Geography Faculty Publications

No abstract provided.

Impact Of Business Analytics And Enterprise Systems On Managerial Accounting, Deniz Appelbaum, Alexander Kogan, Miklos Vasarhelyi, Zhaokai Yan

Department of Accounting and Finance Faculty Scholarship and Creative Works

The nature of management accountants' responsibility is evolving from merely reporting aggregated historical value to also including organizational performance measurement and providing management with decision related information. Corporate information systems such as enterprise resource planning (ERP) systems have provided management accountants with both expanded data storage power and enhanced computational power. With big data extracted from both internal and external data sources, management accountants now could utilize data analytics techniques to answer the questions including: what has happened (descriptive analytics), what will happen (predictive analytics), and what is the optimized solution (prescriptive analytics). However, research shows that the nature and …

A Systematic Literature Review: Existing Hospitality & Tourism Research On Big Data, Jiaojiao Song

UNLV Theses, Dissertations, Professional Papers, and Capstones

Big Data has been in the eye of storm in all walks of live. Since the tourism industry is able to generate tons of data each day, Big Data has caught the attention of scholars and professionals of the industry. People might hear of Big Data here and there, yet are they clear about what Big Data means? Does Big Data refer to a certain amount data or a technology to acquire information to support evidenced decision?

Unfortunately there is no general consensus in academic area according to the book, Big Data: Principals and Paradigms (Buyya, Calheiros, & Dastjerdi, 2016) …

Community Data Analytics: Localized Data Analysis And Decision Modeling In The Era Of ‘Big Data’ And ‘Smart Cities’, Michael P. Johnson Jr.

Michael P. Johnson

Big Data And The Perceived Expectations Gap In Digital Authentication Processes, Thomas Calderon, Colin Onita

Faculty Publications

Perceptions of the security and efficacy of technological innovations significantly affect behavioral intentions and the eventual diffusion of such innovations in organizations and the broader society. This paper uses Twitter as a data source and a big data analysis tool to investigate the public’s perceptions of current authentication methods in financial institutions. This data source has not been used previously in the literature to examine perceptions of authentication methods. We focus on the financial sector because of its high vulnerability, the extensive use of information technology in both products and value chain (i.e., its high business information intensity), and the …

Semantic Inference On Clinical Documents: Combining Machine Learning Algorithms With An Inference Engine For Effective Clinical Diagnosis And Treatment, Shuo Yang, Ran Wei, Jingzhi Guo, Lida Xu

Information Technology & Decision Sciences Faculty Publications

Clinical practice calls for reliable diagnosis and optimized treatment. However, human errors in health care remain a severe issue even in industrialized countries. The application of clinical decision support systems (CDSS) casts light on this problem. However, given the great improvement in CDSS over the past several years, challenges to their wide-scale application are still present, including: 1) decision making of CDSS is complicated by the complexity of the data regarding human physiology and pathology, which could render the whole process more time-consuming by loading big data related to patients; and 2) information incompatibility among different health information systems (HIS) …

Analytics, Innovation, And Organizational Adaptation, Gerard George, Yimin Lin

Research Collection Lee Kong Chian School Of Business

With the advent of big data, organizations are integrating powerful computing tools into their organizational processes to drive efficiencies and improve service delivery. Yet, at the heart of this conversation lies the role of analytics and big data in innovation within and across organizations. In this article, we provide a stylistic model of the role of analytics in innovation and call for further research on the underlying processes, contingencies, and outcomes.

Proactive It Incident Prevention: Using Data Analytics To Reduce Service Interruptions, Mark G. Malley

Walden Dissertations and Doctoral Studies

The cost of resolving user requests for IT assistance rises annually. Researchers have demonstrated that data warehouse analytic techniques can improve service, but they have not established the benefit of using global organizational data to reduce reported IT incidents. The purpose of this quantitative, quasi-experimental study was to examine the extent to which IT staff use of organizational knowledge generated from data warehouse analytical measures reduces the number of IT incidents over a 30-day period, as reported by global users of IT within an international pharmaceutical company headquartered in Germany. Organizational learning theory was used to approach the theorized relationship …