3D and Immersive Interfaces for Business Intelligence: The Case of OLAP

Lafon, Sebastien; Bouali, Fatma; Guinot, Christiane; Venturini, Gilles

doi:10.1109/iv.2013.36

Cited by 5 publications

(5 citation statements)

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“…Wright [47] Proprietary Case Study from portfolio management, derivatives management, customer credit scores Gresh and Kelton [78] Proprietary Private IBM business by-product data Eick [79] Proprietary Log data from web servers used to analyse the efficiency of their website Burkhard [23] Proprietary Case study from Swiss Federal Institute of Technology using business strategy data Vliegen et al [48] Proprietary Unspecified business data Keim et al [80] Proprietary Transaction datasets Otsuka et al [20] Proprietary Digital nametags collect employee interaction data Sedlmair et al [24] Survey Existing software evaluation Kandel et al [18] Proprietary Interview Study with industry experts Du et al [70] Survey A survey of business process visualisation literature Aigner [25] Proprietary Text from interview study Broeksema et al [71] Proprietary Decision model data Bai et al [49] Proprietary Geospatial data for utility network coverage Lafon et al [26] Proprietary User Study of unspecified business data visualisation Nicholas et al [50] Proprietary Private customer survey database from automotive company Roberts et al [51] Proprietary Private call centre interaction database Ghooshchi et al [72] Proprietary Business Processes from undefined source Kumar and Belwal [52] Public Multiple public data sources looking at different aspects of a business Bachhofner et al [73] Proprietary Business processes from industry contacts Lea et al [74] Proprietary Business process data was used alongside simulated data to test prototypes Roberts et al [53] Proprietary Call centre event data from industry partner…”

Section: Classification Paper Ref Access Descriptionmentioning

confidence: 99%

“…The secondary classification used in the survey is shown in Table 1. Aigner [25] Broeksema et al [71] Bai et al [49] Lafon et al [26] Ferreira et al [54] Basole et al [58] Hao et al [42] 2014 Nicholas et al [50] Basole [76] Deligiannidis and Noyes [59] Basole and Bellamy [77] Lu et al [35] Shi et al [36] Rodden [84] Yaeli et al [21] Saitoh [43] 2015 Keahey [29] Basole et al [60] Dou et al [32] Kameoka et al [66] Nair et al [85] 2016 Roberts et al [51] Liu et al [81] Iyer and Basole [61] Basole et al [31] Wu et al [67] Nagaoka et al [22] Sijtsma et al [37] 2017 Ghooshchi et al [72] Kumar and Belwal [52] Bachhofner et al [73] Ramesh et al [34] Schotter et al [62] Kang et al [69] Fayoumi et al [44] 2018 Lea et al [74] Roberts et al [53] Basole et al [63] Sathiyanarayanan et al [68] Haleem et al [45] Saga and Yagi [46] Primary Data as Intentional, Active Digital Collection (CB): The following research conveys geo-location data collected through hardware that is used to track customer be...…”

Section: Customer Behaviour (Cb)mentioning

confidence: 99%

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Visualising Business Data: A Survey

Roberts

Laramee

2018

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A rapidly increasing number of businesses rely on visualisation solutions for their data management challenges. This demand stems from an industry-wide shift towards data-driven approaches to decision making and problem-solving. However, there is an overwhelming mass of heterogeneous data collected as a result. The analysis of these data become a critical and challenging part of the business process. Employing visual analysis increases data comprehension thus enabling a wider range of users to interpret the underlying behaviour, as opposed to skilled but expensive data analysts. Widening the reach to an audience with a broader range of backgrounds creates new opportunities for decision making, problem-solving, trend identification, and creative thinking. In this survey, we identify trends in business visualisation and visual analytic literature where visualisation is used to address data challenges and identify areas in which industries use visual design to develop their understanding of the business environment. Our novel classification of literature includes the topics of businesses intelligence, business ecosystem, customer-centric. This survey provides a valuable overview and insight into the business visualisation literature with a novel classification that highlights both mature and less developed research directions.

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Section: Classification Paper Ref Access Descriptionmentioning

confidence: 99%

Section: Customer Behaviour (Cb)mentioning

confidence: 99%

Visualising Business Data: A Survey

Roberts

Laramee

2018

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“…There is still need for multidimensional DW conceptual and logical models and corresponding DBMS that respect all fundamental requirements of OLAP [41] [79] [1] [61] [63]. User interface for OLAP is an important aspect of the DBMS where many areas are still open [47] [70] [78] [35], and where the possibility of directly obtaining state [87], not just attributes, from data, i.e. data mining, represents a promising research avenue.…”

Section: E Conclusionmentioning

confidence: 99%

Universal Data Warehouse Management System Research Proposal

2023

International Conference Proceedings IICSET-23, ACBES-23 &Amp; LMSSH-23 Dec. 14-15, 2023 Istanbul (Turkiye)

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“…Diferentes variables son simbolizadas mediante su tamaño y color, según se puede ver en la Figura 4. DIVE-ON (Data mining in an Immersed Virtual Environment Over a Network) es un entorno que utiliza un sistema VR llamado CAVE para sumergir al usuario en los datos a través del uso de pantallas estereoscópicas, y guantes con sensores [33] Figura 4: Interface de usuario de Miner3D…”

Section: Decisionesunclassified

“…Un estudio más profundo sobre este tipo de interfaces, así como una nueva interface llamada VR4OLAP puede ser encontrado en el trabajo de Lafon et al [33] La demanda de interactividad y la necesidad de sintetizar grandes cantidades de datos han provocado que las técnicas de analítica visual hayan aumentado su presencia en los sistemas BI de mayor peso en el mercado. El resto asumido es el de mostrar los datos de forma interactiva, comprensible y preparada para ser utilizada en la toma de decisiones.…”

Section: Decisionesunclassified

Importance of visualization usage in enterprise decision making environements

Cota

Castro

Dominguez

2014

2014 9th Iberian Conference on Information Systems and Technologies (CISTI)

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Resumen -El rol de las herramientas de visualización ha adquirido gran preponderancia dentro del análisis de datos y soporte a toma de decisiones en entornos empresariales. El crecimiento de los canales de generación de información llega a provocar una sobrecarga que pone en riesgo la capacidad de análisis de los diferentes actores del órgano empresarial. Para afrontar este problema, los principales sistemas de Business Intelligence del mercado comienzan a hacer uso de técnicas de visualización para proveer mecanismos que permitan al usuario ver y comprender grandes volúmenes abstractos de información. Sin embargo, el componente humano de la toma de decisiones hace que el buen aprovechamiento de la analítica visual depende en gran medida de la cultura organizativa de cada empresa.. Palabras Clave -Análisis Visual, Sistemas de Soporte a Decisiones, Business Intelligence.Abstract -Visualization tools have acquired a dominance roll within the data analysis and decision making support systems inside enterprise environments. Growth of information generation channels gets to bring an overload that jeopardizes analysis capacity in the different actors from the enterprise organ. In order to confront this problem, the main Business Intelligence market systems begin to brand use of visualization techniques to provide mechanisms that allow user to see and understand great volumes of abstract information. Nevertheless, decision making's human component causes that the good advantage of visual analytics depends to a great extent on the company's organizational culture. I. INTRODUCCIÓNLas empresas son organismos que a través de la administración de recursos, capital y trabajo [1] realizan su actividad en un entorno social, liberando soluciones de alto valor agregado que le permiten obtener resultados y generar beneficios. En un mundo globalizado, la incesante variabilidad de los mercados impone una constante toma de decisiones por parte de los gestores. Las decisiones, por lo general, desembocan en directivas de planificación, organización, dirección o control [2] que son ejecutadas con la intención de cumplir los objetivos marcados.Una decisión supone una irrevocable disposición de recursos [3] y la optimización de los mismos es fundamental para alcanzar las metas establecidas. Dada esta premisa, se puede afirmar que el análisis de las actividades corporativas es una disciplina inherente a la gestión empresarial y que los sistemas de soporte a la toma de decisiones forman parte, en mayor o menor medida, del ecosistema natural de cualquier empresa.En los últimos años, hitos como la banalización de Internet y los dispositivos móviles, la popularidad de las redes sociales o el asentamiento del comercio electrónico han provocado que el crecimiento de los canales de generación de información, junto con su diversidad y heterogeneidad, genere una paradoja que los sistemas de informáticos deben esforzarse en resolver: Los datos son recibidos desde cada vez más fuentes, con mayor frecuencia y recopilados con tasas de almacenamiento má...

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3D and Immersive Interfaces for Business Intelligence: The Case of OLAP

Cited by 5 publications

References 0 publications

Visualising Business Data: A Survey

Visualising Business Data: A Survey

Universal Data Warehouse Management System Research Proposal

Importance of visualization usage in enterprise decision making environements

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