Correlates of the internal audit function’s use of data analytics in the big data era: Global evidence

2021 ◽  
Vol 42 ◽  
pp. 100357
Author(s):  
Romina Rakipi ◽  
Federica De Santis ◽  
Giuseppe D'Onza
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Internal Audit ◽  
Use Of Data ◽  
Global Evidence

Improving the use of analytics and big data by changing the decision-making culture

2017 ◽  
Vol 55 (10) ◽  
pp. 2074-2088 ◽  
Author(s):  
Jane Elisabeth Frisk ◽  
Frank Bannister
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analytics ◽  
Design Approach ◽  
Action Research Project ◽  
Content Type ◽  
Use Of Data ◽  
Support Organizations ◽  
Novel Approach ◽  
Using Data

Purpose Evolving digital technologies continue to enable new ways to collect and analyze data and this has led some researchers to claim that skillful use of data analytics and big data can radically improve a company’s performance, but that in order to achieve such improvements managers need to change their decision-making culture and to increase the degree of collaboration in the decision-making process. The purpose of this paper is to create an increased understanding of how a decision-making culture can be changed by using a design approach. Design/methodology/approach The paper presents an action research project in which the authors use a design approach. Findings By adopting a design approach organizations can change their decision-making culture, increase the degree of collaboration and also reduce the influence of power and politics on their decision-making. Research limitations/implications This paper proposes a new approach to changing a decision-making culture. Practical implications Using data analytics and big data, a design approach can support organizations change their decision-making culture resulting in better and more effective decisions. Originality/value This paper bridges design and decision-making theory in a novel approach to an old problem.

scholarly journals Big data analytics in internal audit

Pressacademia ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 260-262
Author(s):  
Idil Kaya ◽  
Destan Halit Akbulut ◽  
Koray Ozoner
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Internal Audit

Big Data and Its Role in Facilitating the Visualization of Financial Analytics

2018 ◽  
pp. 704-722
Author(s):  
Iman Raeesi Vanani ◽  
Maziar Shiraj Kheiri
Keyword(s):  
Big Data ◽  
Global Economy ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Accounting Measurement ◽  
Use Of Data ◽  
Accounting Environment ◽  
Using Data ◽  
And Function ◽  
Support Decision Making

The business use of data analytics is growing rapidly in the accounting environment. Similar to many new systems that involve accounting information, data analytics has fundamentally changed task based processes particularly those tasks that provide inference, prediction and assurance to decision makers. Big Data analytics is the process of inspecting, cleaning, transforming, and modeling Big Data to discover and communicate useful information and patterns, suggest conclusions, and support decision making. Big Data now pervades every sector and function of the global economy. These essays focus on the uses and challenges of Big Data in accounting (measurement) and auditing (assurance). The objective of this chapter is to examine how Big Data analytics will impact the accounting and auditing environment. This is important to practitioners as well as academics because they will be using data analytics in accounting and auditing tasks and will need to have an in-depth familiarity with financial analytics to effectively accomplish these tasks and make effective and efficient decisions.

An Introduction to Big Data and Democracy

2020 ◽  
pp. 1-10
Author(s):  
Kevin Macnish ◽  
Jai Galliott
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Donald Trump ◽  
Use Of Data

This chapter introduces the book through highlighting recent cases of ethical and democratic concern arising through the use of data analytics (so-called “big data”). The aftermath of the election of Donald Trump and the Brexit referendum were dogged by claims that the elections had been manipulated through microtargeting by companies such as Cambridge Analytica in favour of the winning parties. The Introduction concludes with an overview of each following chapter in the book.

Effects of digitalisation of organisations on internal audit activities and practices

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nathanaël Betti ◽  
Gerrit Sarens ◽  
Ingrid Poncin
Keyword(s):  
Data Analytics ◽  
Internal Audit ◽  
Future Research ◽  
Content Type ◽  
Internal Auditors ◽  
Audit Planning ◽  
Use Of Data ◽  
The Us ◽  
The Usa ◽  
Legal Contexts

Purpose This paper aims to investigate how the internal audit function (IAF) modifies its activities and practices in relation to the digitalisation the organisation. This paper specifically examines the use of data analytics and the performance of consulting activities by internal auditors. Design/methodology/approach This paper is based on a survey conducted with 82 chief audit executives based in the USA and members of the institute of internal auditors. Findings Results indicate a positive relation between the organisation’s level of digitalisation and the use of data analytics by internal auditors during their missions. Results also indicate that the organisation’s level of digitalisation has an indirect effect on the proportion of the internal audit planning dedicated to consulting activities. Specifically, the use of data analytics mediates the relationship between the organisation’s level of digitalisation and the proportion of the internal audit planning dedicated to consulting activities. Research limitations/implications This research was conducted amongst internal auditors based in the US Future research could investigate the insights of other internal audit stakeholders and investigate different legal contexts. Practical implications Results show that digitalisation increases the use of data analytics by internal auditors and the performance of consulting activities. The results, therefore, highlight the importance of these two aspects for the IAF to continue to bring value to organisations. Originality/value This research provides more insights on internal audit working practices. The digitalisation of the organisation leads the IAF to use more data analytics and perform more consulting activities.

scholarly journals Big data analytics - towards the enrichment of content tourism for revitalization of Japanese rural area

2018 ◽  
Vol 169 ◽  
pp. 01008 ◽  
Author(s):  
Ali Bakdur ◽  
Fumito Masui ◽  
Michal Ptaszynski
Keyword(s):  
Big Data ◽  
Rural Areas ◽  
Data Analytics ◽  
Data Science ◽  
Public Awareness ◽  
Big Data Analytics ◽  
Tourism Industry ◽  
Analysis Model ◽  
Travel And Tourism ◽  
Use Of Data

Japan's domestic travel and tourism industry expenditure has been declining gradually since 1998 (from 33.5 in 1998 to 21.6 trillion JPY in 2016). Our research purpose is to construct a data analysis model to transform the collected data to a meaningful graphical format by using big data analytics techniques to discover anomalies and sustainable development possibilities for economy and tourism of Japan's rural areas, with a particular focus on the prefecture of Hokkaido, subprefecture of Okhotsk. To strengthen the reliability of this model we apply popular Monte Carlo simulation combined with Bayesian statistic and implement it on an Apache Spark platform to acquire results within the span of the study. Through this research, we focus on observing and analyzing interests, expectations and tendencies of Japanese people living in rural areas. From such collected information, we can obtain reasons for the decline of this sector’s impact on Japan’s economy. Measuring public awareness has become more efficient since the content generator role has been passed on to ordinary people. Therefore, the analysis of Big Data with the use of data science techniques has become important to comprehend human behavior from multiple points of view, including the scientific, economic, political, historical and sociological.

scholarly journals The use of Big Data Analytics in healthcare

2022 ◽  
Vol 9 (1) ◽  
Author(s):  
Kornelia Batko ◽  
Andrzej Ślęzak
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
New Technologies ◽  
Health Management ◽  
Big Data Analytics ◽  
Structural Data ◽  
Unstructured Data ◽  
Clinical Area ◽  
Use Of Data ◽  
Medical Facilities

AbstractThe introduction of Big Data Analytics (BDA) in healthcare will allow to use new technologies both in treatment of patients and health management. The paper aims at analyzing the possibilities of using Big Data Analytics in healthcare. The research is based on a critical analysis of the literature, as well as the presentation of selected results of direct research on the use of Big Data Analytics in medical facilities. The direct research was carried out based on research questionnaire and conducted on a sample of 217 medical facilities in Poland. Literature studies have shown that the use of Big Data Analytics can bring many benefits to medical facilities, while direct research has shown that medical facilities in Poland are moving towards data-based healthcare because they use structured and unstructured data, reach for analytics in the administrative, business and clinical area. The research positively confirmed that medical facilities are working on both structural data and unstructured data. The following kinds and sources of data can be distinguished: from databases, transaction data, unstructured content of emails and documents, data from devices and sensors. However, the use of data from social media is lower as in their activity they reach for analytics, not only in the administrative and business but also in the clinical area. It clearly shows that the decisions made in medical facilities are highly data-driven. The results of the study confirm what has been analyzed in the literature that medical facilities are moving towards data-based healthcare, together with its benefits.

scholarly journals Big Data under Obama and Trump: The Data-Fueled U.S. Presidency

2018 ◽  
Vol 6 (4) ◽  
pp. 29-39
Author(s):  
Barbara Trish
Keyword(s):  
Big Data ◽  
Performance Management ◽  
Data Analytics ◽  
The Political ◽  
Evidence Based ◽  
Electoral Campaigns ◽  
Use Of Data ◽  
Drone Strikes ◽  
The U.S ◽  
Trump Administration

The much-heralded use of data, analytics, and evidence-based decisions marks the U.S. presidency, wherein many processes and decisions are structured by the analysis of data. An approach with historical precedent, reliance on data was prominent under Obama, and is even under Trump, despite signals to the contrary. This article examines three cases from the Obama era: microtargeting in electoral campaigns, performance management in government, and signature drone strikes employed by the national security apparatus. It also reflects on the early Trump administration. The processes described are highly dependent on data, technically big data in two instances. The article examines the cases both on their own terms and in the context of a critical lens that directs attention to the political economy of the data. The analysis helps unpack the allure of data and analytics as well as the challenges in structuring an environment with a measured approach to data and big data, which would examine both their potential and drawback.

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