scholarly journals 5S Dashboard Design Principles for Self-Service Business Intelligence Tool User

2018 ◽  
Vol 1 (1) ◽  
pp. 5-19
Author(s):  
Ching-Yi Lin ◽  
Fu-Wen Liang ◽  
Sheng-Tun Li ◽  
Tsung-Hsueh Lu
Keyword(s):  
Health Care ◽  
Business Intelligence ◽  
Design Principles ◽  
Research Approach ◽  
It Professionals ◽  
The Public ◽  
Service Business ◽  
Quality Of Diabetes Care ◽  
Self Service ◽  
Using Data

Non–information technology (IT) professionals and nonexpert casual users are increasingly adopting self-service business intelligence (SSBI) tools (such as Tableau, Qlik, and Power BI) to create data visualization dashboards. This study identified the most relevant dashboard design principles for SSBI tool users. The research approach included organizing a focus group in which most of the participants were non-IT professionals in health care, extracting recommended principles from the literature, applying these recommended principles by using data on quality of diabetes care to design relevant dashboards, and proposing the following 5S dashboard design principle framework: 1) seeing both the forest and trees, 2) simplicity through self-selection, 3) simplicity through significance, 4) simplicity through synthesis, and 5) storytelling. The third and fourth principles are novel and provide solutions to decision-making problems (such as conflicting results from excessive and discordant indicators) encountered by health care professional in the public sector as well as in other domains. The 5S dashboard design principles are easily memorized and practical and thus enable non-IT professionals and nonexpert casual users to design insightful dashboards efficiently by using SSBI tools.

Using of data science in healthcare

2021 ◽  
pp. 149-156
Author(s):  
Ihor Ponomarenko ◽  
Oleksandra Lubkovska
Keyword(s):  
Machine Learning ◽  
Health Care ◽  
Business Intelligence ◽  
Data Science ◽  
Large Data ◽  
Science Methods ◽  
Medical Field ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Using Data

The subject of the research is the approach to the possibility of using data science methods in the field of health care for integrated data processing and analysis in order to optimize economic and specialized processes The purpose of writing this article is to address issues related to the specifics of the use of Data Science methods in the field of health care on the basis of comprehensive information obtained from various sources. Methodology. The research methodology is system-structural and comparative analyzes (to study the application of BI-systems in the process of working with large data sets); monograph (the study of various software solutions in the market of business intelligence); economic analysis (when assessing the possibility of using business intelligence systems to strengthen the competitive position of companies). The scientific novelty the main sources of data on key processes in the medical field. Examples of innovative methods of collecting information in the field of health care, which are becoming widespread in the context of digitalization, are presented. The main sources of data in the field of health care used in Data Science are revealed. The specifics of the application of machine learning methods in the field of health care in the conditions of increasing competition between market participants and increasing demand for relevant products from the population are presented. Conclusions. The intensification of the integration of Data Science in the medical field is due to the increase of digitized data (statistics, textual informa- tion, visualizations, etc.). Through the use of machine learning methods, doctors and other health professionals have new opportunities to improve the efficiency of the health care system as a whole. Key words: Data science, efficiency, information, machine learning, medicine, Python, healthcare.

scholarly journals Fusion Cubes

2013 ◽  
Vol 9 (2) ◽  
pp. 66-88 ◽  
Author(s):  
Alberto Abelló ◽  
Jérôme Darmont ◽  
Lorena Etcheverry ◽  
Matteo Golfarelli ◽  
Jose-Norberto Mazón ◽  
...  
Keyword(s):  
Business Intelligence ◽  
Decision Process ◽  
Decision Makers ◽  
Related Research ◽  
Service Business ◽  
Short Lifespan ◽  
Research Challenges ◽  
Self Service ◽  
Core Idea ◽  
And Storage

Self-service business intelligence is about enabling non-expert users to make well-informed decisions by enriching the decision process with situational data, i.e., data that have a narrow focus on a specific business problem and, typically, a short lifespan for a small group of users. Often, these data are not owned and controlled by the decision maker; their search, extraction, integration, and storage for reuse or sharing should be accomplished by decision makers without any intervention by designers or programmers. The goal of this paper is to present the framework we envision to support self-service business intelligence and the related research challenges; the underlying core idea is the notion of fusion cubes, i.e., multidimensional cubes that can be dynamically extended both in their schema and their instances, and in which situational data and metadata are associated with quality and provenance annotations.

Self-Service Business Intelligence Adoption in Business Enterprises

2017 ◽  
Vol 13 (3) ◽  
pp. 65-85 ◽  
Author(s):  
Mohammad Daradkeh ◽  
Radwan Moh'd Al-Dwairi
Keyword(s):  
Technology Acceptance ◽  
Business Intelligence ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
System Quality ◽  
Service Business ◽  
Business Enterprises ◽  
Self Service ◽  
Analysis Quality

Despite the growing popularity of self-service business intelligence (SSBI) tools, empirical research that investigates their acceptance by business professionals is still scarce. This paper presents and tests an integrated model of the antecedents of users' acceptance of SSBI tools in business enterprises. The proposed model is developed based on the technology acceptance model (TAM) and incorporating information and system quality from DeLone and McLean IS success model. It also includes an important factor from the business intelligence literature called analysis quality. To test the model, data were collected through a questionnaire survey from 331 business users working in a variety of industries in Jordan. Data were analysed using structural equation modeling (SEM) techniques. The results demonstrated that the three quality factors– information quality, system quality and analysis quality – are key antecedents of perceived usefulness and ease of use, which in turn were found to be strong predictors of users' intention to use SSBI tools. The findings of this study provide several implications for research and practice, and thus should help in the design and deployment of more user-accepted SSBI tools.

scholarly journals A analytics study Mapping Study of Collaborative business intelligence and self-service

2021 ◽  
Vol 9 (12) ◽  
pp. 1032-1037
Author(s):  
Tanmayee Parbat
Keyword(s):  
Business Intelligence ◽  
Design Science ◽  
Science Research ◽  
Research Approach ◽  
Knowledge Database ◽  
Architecture Model ◽  
Service Oriented ◽  
Decision Making Processes ◽  
Self Service ◽  
Self Learning

Abstract: Self-service Business Intelligence (SSBI) is an emerging topic for many companies. Casual users should be enabled to independently build their own analyses and reports. This accelerates and simplifies the decision-making processes. Although recent studies began to discuss parts of a self-service environment, none of these present a comprehensive architecture. Following a design science research approach, this study proposes a new self-service oriented BI architecture in order to address this gap. Starting from an in-depth literature review, an initial model was developed and improved by qualitative data analysis from interviews with 18 BI and IT specialists form companies across different industries. The proposed architecture model demonstrates the interaction between introduced self-service elements with each other and with traditional BI components. For example, we look at the integration of collaboration rooms and a self-learning knowledge database that aims to be a source for a report recommender. Keywords: Business Intelligence, Big Data, Architecture, Self-Service, Analytics

scholarly journals User-Related Challenges of Self-Service Business Intelligence

2020 ◽  
pp. 1-15
Author(s):  
Christian Lennerholt ◽  
Joeri Van Laere ◽  
Eva Söderström
Keyword(s):  
Business Intelligence ◽  
Service Business ◽  
Self Service

scholarly journals ACCOUNTABILITY OF MADRASAH SUPERVISORS IN CAREER DEVELOPMENT HEAD OF MADRASAH TSANAWIYAH NEGERI IN JAMBI PROVINCE

2019 ◽  
Vol 7 (7) ◽  
pp. 173-182
Author(s):  
Mukhtar ◽  
Risnita ◽  
Edy Kusnadi
Keyword(s):  
Career Development ◽  
Skills Training ◽  
Growth Direction ◽  
Qualitative Approach ◽  
Islamic Education ◽  
Research Approach ◽  
The Public ◽  
Innovative Work ◽  
Data Validity ◽  
Using Data

This research is motivated by the pessimism of the Head of Islamic Education in improving their careers to a higher level. This situation is inseparable from the role and guidance carried out by the Madrasah supervisor. This study aims to: 1) Know the supervision of Madrasah that have not been accountable in fostering the career of the head of the Madrasah Tsanawiyah Negeri in Jambi Province. 2) Determine the accountability of supervisors of Madrasah Tsanawiyah Negeri in Jambi Province. 3) Knowing the career of the head of the Madrasah Tsanawiyah Negeri in Jambi Province. 4) Knowing the accountability of madrasah supervisors in the career development of Madrasah heads in Jambi Province.The research approach used is a descriptive qualitative approach. The technique of collecting data uses observation, interviews, and documentation. Data analysis using the Creswell model and data validity techniques using data triangulation. The results of the research on the accountability of madrasah supervisors can be seen from the existence of transparency, liability, controllability, responsibility, responsiveness, ability, development, skills, training, and care. Career Head of Madrasah can be seen from the implementation of the stages of planning, growth, direction, exploration, development, stabilization, innovative work, professional ability, promotion, promotion, and appreciation. The conclusion is that the accountability of madrasah supervisors can develop the career of the Head of the Public Madrasah Tsanawiyah in Jambi Province. The implication of this study is that the accountability of madrasah supervisors is able to develop the career of the Madrasah Chief.

scholarly journals A Study of Analysis and Trends for Embedded Business Intelligence Market

2021 ◽  
Vol 9 (12) ◽  
pp. 1025-1031
Author(s):  
Tanmayee Tushar Parbat
Keyword(s):  
Business Intelligence ◽  
Design Science ◽  
Science Research ◽  
Research Approach ◽  
Knowledge Database ◽  
Architecture Model ◽  
Service Oriented ◽  
Decision Making Processes ◽  
Self Service ◽  
Self Learning

Abstract: Self-service Business Intelligence (SSBI) is an emerging topic for many companies. Casual users should be enabled to independently build their own analyses and reports. This accelerates and simplifies the decision-making processes. Although recent studies began to discuss parts of a self-service environment, none of these present a comprehensive architecture. Following a design science research approach, this study proposes a new self-service oriented BI architecture in order to address this gap. Starting from an in-depth literature review, an initial model was developed and improved by qualitative data analysis from interviews with 18 BI and IT specialists form companies across different industries. The proposed architecture model demonstrates the interaction between introduced self-service elements with each other and with traditional BI components. For example, we look at the integration of collaboration rooms and a self-learning knowledge database that aims to be a source for a report recommender. Keywords: Business Intelligence, Big Data, Architecture, Self-Service, Analytics

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