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A Business Intelligence Dashboard Design Approach to Improve Data Analytics and Decision Making
(CEUR Workshop Proceedings, 2020) Orlovskyi, D. L.; Kopp, A. M.
This paper considers a problem of dashboard design in order to improve data analytics and decision making as business intelligence capabilities. Essentials of data warehouses and data marts used as data sources for business intelligence activities are briefly outlined, and the star schema data structure is considered as the most widely used. Data visualization is considered from the perspective of proper visualization graphs and charts selection. It is extremely vital for designed dashboards, since inappropriate visuals may mislead users and shift their focus to wrong things. Bar charts, line charts, and pie charts are considered as the most common visualization graphs. Proposed approach includes two phases: dataset preparation and dataset analysis. While dataset preparation is mostly focused on star schema transformation into flat structures, dataset analysis phase proposes recommendations on which visualizations may be placed on a designed dashboard. In order to propose such recommendations, threshold values of dataset sizes are used. A dashboard design process, which is considered as the baseline of the proposed dashboard design approach, is outlined. Sample dataset in considered, five data subsets are prepared and recommendations on visualization charts for these datasets, which may be placed on a dashboard, are proposed. Obtained results are discussed, conclusions are made, as well as the further research objectives in this field are formulated.
An Approach to Forming Dashboards for Business Process Indicators Analysis using Fuzzy and Semantic Technologies
(CEUR Workshop Proceedings, 2018) Kopp, A. M.; Orlovskyi, D. L.
This article considers development of the approach to forming dashboards for business process indicators analysis. The approach idea is based on the dashboard design problem, outlined in analyzed works, which propose a lot of recommendations and best practices, but have a lack of formal approaches to dashboard design definition for specific business process indicators. This study considers application of fuzzy and semantic technologies in order to provide description and analysis of relations between analyzed business process indicators, indicator’s types, and visualization tools. It also considers event log processing of a workflow system, used to execute business processes, which indicators are measured. As a result of implementation and application of the proposed approach, recommendations for a dashboard’s design, based on specific business processes and their performance indicators to be analyzed, can be obtained and implemented. The theoretical essentials, workflow scheme, and early results of the proposed approach are given, future research is outlined.
A business intelligence dashboard design approach to improve data analytics and decision making
(Stylos, 2020) Orlovskyi, D. L.; Kopp, A. M.
This paper considers a problem of dashboard design, since usage of inappropriate visuals may mislead users and shift their focus to wrong things. Bar charts, line charts, and pie charts are considered as the most common visualization graphs. Proposed approach includes dataset preparation and analysis phases. While dataset preparation phase is mostly focused on star schema transformation into flat structures, dataset analysis phase proposes recommendations on which visualizations may be placed on a designed dashboard.
Development of a model and a software solution to support the analytical dashboards design problem
(Національний технічний університет "Харківський політехнічний інститут", 2020) Orlovskyi, D. L.; Kopp, A. M.; Kondratiev, V. Yu.
This research paper considers the problem of dashboard design as part of the Business Process Management lifecycle, where it is become necessary to monitor and control the current state of the organizational business processes. Therefore, designed dashboards should fully correspond to the features of the considered business processes, such as Key Performance Indicators and possible stakeholders, which are considered here as users of the developed Business Intelligence dashboard application. At the same time, according to the state-of-the-art in the field of data visualization, it is required to choose data visualization techniques, which are clear, easy interpretable, space efficient, attractive, and legible. In general, the dashboard design problem requires placing various visualization tools in a relatively small place, such as a screen of a computer, a laptop, a tablet, or even a smart phone, while keeping them accessible and easy to understand. At first, as part of the related work review and analysis, we have considered the core architecture of the dashboards and reporting applications. It is outlined that modern dashboards might use various big data chunks, such as databases of enterprise information systems of different types, spreadsheets data, and even unstructured documents. In order to summarize all the raw data from these data sources, the Data Warehouse should be built and, moreover, it should correspond to the metrics and indicators of business processes that should be demonstrated on a dashboard. We have also considered main principles, common mistakes, and graphs and charts that might be used to design a dashboard for business analytics purposes. Using the existing research in this field, the levels of informativeness were defined for each visualization tool, as well as the best practices of mapping various data types to graphs and charts are outlined. Proposed model of the da shboard design is based on the mathematical optimization. It is used to provide recommendations on which visualization tool should be used to display a certain Key Performance Indicator on a dashboard that corresponds to a certain user role. Development and usage of the software solution that implements the proposed model is outlined, as well as the obtained results of validation of the proposed software solution are shown and discussed.

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