Linking business analytics to decision making effectiveness: a path model analysis

While business analytics is being increasingly used to gain data-driven insights to support decision making, little research exists regarding the mechanism through which business analytics can be used to improve decision-making effectiveness (DME) at the organizational level. Drawing on the information processing view and contingency theory, this paper develops a research model linking business analytics to organizational DME. The research model is tested using structural equation modeling based on 740 responses collected from U.K. businesses. The key findings demonstrate that business analytics, through the mediation of a data-driven environment, positively influences information processing capability, which in turn has a positive effect on DME. The findings also demonstrate that the paths from business analytics to DME have no statistical differences between large and medium companies, but some differences between manufacturing and professional service industries. Our findings contribute to the business analytics literature by providing useful insights into business analytics applications and the facilitation of data-driven decision making. They also contribute to manager's knowledge and understanding by demonstrating how business analytics should be implemented to improve DM

Facilitating insight into a simulation model using visualization and dynamic model previews

This paper shows how model simplification, by replacing iterative steps with unitary predictive equations, can enable dynamic interaction with a complex simulation process. Model previews extend the techniques of dynamic querying and query previews into the context of ad hoc simulation model exploration. A case study is presented within the domain of counter-current chromatography. The relatively novel method of insight evaluation was applied, given the exploratory nature of the task. The evaluation data show that the trade-off in accuracy is far outweighed by benefits of dynamic interaction. The number of insights gained using the enhanced interactive version of the computer model was more than six times higher than the number of insights gained using the basic version of the model. There was also a trend for dynamic interaction to facilitate insights of greater domain importance

Scholarly insight Spring 2018: a Data wrangler perspective

In the movie classic Back to the Future a young Michael J. Fox is able to explore the past by a time machine developed by the slightly bizarre but exquisite Dr Brown. Unexpectedly by some small intervention the course of history was changed a bit along Fox’s adventures. In this fourth Scholarly Insight Report we have explored two innovative approaches to learn from OU data of the past, which hopefully in the future will make a large difference in how we support our students and design and implement our teaching and learning practices. In Chapter 1, we provide an in-depth analysis of 50 thousands comments expressed by students through the Student Experience on a Module (SEAM) questionnaire. By analysing over 2.5 million words using big data approaches, our Scholarly insights indicate that not all student voices are heard. Furthermore, our big data analysis indicate useful potential insights to explore how student voices change over time, and for which particular modules emergent themes might arise. In Chapter 2 we provide our second innovative approach of a proof-of-concept of qualification path way using graph approaches. By exploring existing data of one qualification (i.e., Psychology), we show that students make a range of pathway choices during their qualification, some of which are more successful than others. As highlighted in our previous Scholarly Insight Reports, getting data from a qualification perspective within the OU is a difficult and challenging process, and the proof-of-concept provided in Chapter 2 might provide a way forward to better understand and support the complex choices our students make. In Chapter 3, we provide a slightly more practically-oriented and perhaps down to earth approach focussing on the lessons-learned with Analytics4Action. Over the last four years nearly a hundred modules have worked with more active use of data and insights into module presentation to support their students. In Chapter 3 several good-practices are described by the LTI/TEL learning design team, as well as three innovative case-studies which we hope will inspire you to try something new as well. Working organically in various Faculty sub-group meetings and LTI Units and in a google doc with various key stakeholders in the Faculties, we hope that our Scholarly insights can help to inform our staff, but also spark some ideas how to further improve our module designs and qualification pathways. Of course we are keen to hear what other topics require Scholarly insight. We hope that you see some potential in the two innovative approaches, and perhaps you might want to try some new ideas in your module. While a time machine has not really been invented yet, with the increasing rich and fine-grained data about our students and our learning practices we are getting closer to understand what really drives our students

Emoto - visualising the online response to London 2012.

In recent years we have moved from data scarcity to data abundance. As a response, a variety of methods have been adopted in art, design, business, science and government to understand and communicate meaning in data through visual form. emoto (emoto2012.org) is one such project, it visualised the online audience response to a major global event, the London 2012 Olympic and Paralympic Games. emoto set out to both give expression to and augment online social phenomena, that are emergent and only recently made possible by access to huge real-time data streams. This report charts the development and release of the project, and positions it in relation to current debates on data and visualisation, for example, around the bias and accessibility of the data, and how knowledge practices are changing in an era of so-called 'big data.

Emoto - visualising the online response to London 2012.

In recent years we have moved from data scarcity to data abundance. As a response, a variety of methods have been adopted in art, design, business, science and government to understand and communicate meaning in data through visual form. emoto (emoto2012.org) is one such project, it visualised the online audience response to a major global event, the London 2012 Olympic and Paralympic Games. emoto set out to both give expression to and augment online social phenomena, that are emergent and only recently made possible by access to huge real-time data streams. This report charts the development and release of the project, and positions it in relation to current debates on data and visualisation, for example, around the bias and accessibility of the data, and how knowledge practices are changing in an era of so-called 'big data.

The role of motivation in regulating the extent to which data visualisation literacy influences business intelligence and analytics use in organisations

Dissertation (MCom (Informatics))--University of Pretoria 2022.The ability to read and interpret visualised data is a critical skill to have in this information age where business intelligence and analytics (BI&A) systems are increasingly used to support decision-making. Data visualisation literacy is seen as the foundation of analytics. Moreover, there is great hype about data-driven analytical culture and data democratisation, where users are encouraged to have wide access to data and fully use BI&A to reap the benefits. Motivation is a stimulant to the richer use of any information system (IS), yet literature provides a limited understanding of the evaluation of data visualisation literacy and the effect of motivation in the BI&A context. Thus, this study aims to explain the role of motivation in regulating the extent to which data visualisation literacy influences BI&A’s exploitative and explorative use in organisations. Data visualisation literacy is measured using six data visualisations that focus on the five cognitive basic intelligent analytical tasks that assess the user's ability to read and interpret visualised data. Two types of motivations are assessed using perceived enjoyment as an intrinsic motivator and perceived usefulness as an extrinsic motivator. The model is tested using quantitative data collected from 111 users, applying Structural Equation Modelling (SEM). The results indicate that intrinsic motivation exerts a positive effect on BI&A exploitative and explorative use while extrinsic motivation has a positive effect on BI&A exploitative use but weakens innovation with a negative effect on explorative use. The results further show an indirect relationship between data visualisation literacy with BI&A use through motivation. In addition, exploitation leads to creativity with exploitation positively being associated with exploration.InformaticsMCom (Informatics)Unrestricte

State of the art 2015: a literature review of social media intelligence capabilities for counter-terrorism

Overview This paper is a review of how information and insight can be drawn from open social media sources. It focuses on the specific research techniques that have emerged, the capabilities they provide, the possible insights they offer, and the ethical and legal questions they raise. These techniques are considered relevant and valuable in so far as they can help to maintain public safety by preventing terrorism, preparing for it, protecting the public from it and pursuing its perpetrators. The report also considers how far this can be achieved against the backdrop of radically changing technology and public attitudes towards surveillance. This is an updated version of a 2013 report paper on the same subject, State of the Art. Since 2013, there have been significant changes in social media, how it is used by terrorist groups, and the methods being developed to make sense of it.  The paper is structured as follows: Part 1 is an overview of social media use, focused on how it is used by groups of interest to those involved in counter-terrorism. This includes new sections on trends of social media platforms; and a new section on Islamic State (IS). Part 2 provides an introduction to the key approaches of social media intelligence (henceforth ‘SOCMINT’) for counter-terrorism. Part 3 sets out a series of SOCMINT techniques. For each technique a series of capabilities and insights are considered, the validity and reliability of the method is considered, and how they might be applied to counter-terrorism work explored. Part 4 outlines a number of important legal, ethical and practical considerations when undertaking SOCMINT work