Collaborative Business Intelligence - Definition
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What is Collaborative Business Intelligence (CBI)?
The term "collaborative" refers to an organized group of people who work towards achieving a common goal. Business intelligence, on the other hand, is defined as a process driven by technology that is used for data analysis and presentation of actionable information that assists executives, managers, and other corporate end-users to make informed business decisions.
Collaborative Business Intelligence (CBI) is a concept that involves the integration of Business Intelligence (BI) and collaborative technological tools in order to support an organization in making new and improved business decisions.
Collaborative Business Interaction tools
Examples of modern collaborative business interaction tools include:
- SAP BusinessObjects, a BI tool that works on its own or as a part of a larger SAP technology stack.
- Geckoboard, a dashboard software that displays key metrics and connects companies to existing software.
- Dundas BI suggests the right data visualizations and gives deep insights to non-analysts.
- Oracle BI, a middleware running on the Oracle business stack that provides businesses with wide-reaching analytics options.
- Sisense combines data directly from SaaS products and databases for analytics for every user.
- Domo unites native connections with data processing software apps.
- Tableau is a leading business intelligence software for data analysts and businesses.
Academic Research on Collaborative Business Intelligence (CBI)
- Structuring collaborative business intelligence: A literature review, Kaufmann, J., & Chamoni, P. (2014, January). Structuring collaborative business intelligence: A literature review. In System Sciences (HICSS), 2014 47th Hawaii International Conference on (pp. 3738-3747). IEEE. Cooperative work in the processes of analysis and decision support currently gains strong attention in the business world. This is motivated by spreading corporate structures and technical developments like social media and network-oriented data storage that encourage the users' comprehension and demand for easy communication about data. This article reflects the state of research in the domain of business intelligence regarding the opening of processes for new data sources and analysts. Existing approaches are often labeled collaborative business intelligence (CBI), but differ heavily in definitions and focus. Therefore, a framework is presented and three main fields for the research of CBI are identified, which encompass internal communication, data storage with (external) partners and data analysis with partners. This article compares the findings with developments on the software market and describes open topics in the research domain.
- Business intelligence solutions for gaining competitive advantage, Muntean, M., & Mircea, G. (2007). Business intelligence solutions for gaining competitive advantage. Informatica Economica Journal, XI, 3, 22-25.
- Advanced collaborative business ICT infrastructures, Rabelo, R. J. (2008). Advanced collaborative business ICT infrastructures. In Methods and Tools for collaborative networked organizations (pp. 337-370). Springer, Boston, MA.
- A survey on recent research in business intelligence, Aruldoss, M., Lakshmi Travis, M., & Prasanna Venkatesan, V. (2014). A survey on recent research in business intelligence. Journal of Enterprise Information Management, 27(6), 831-866.
- Business Intelligence Support Systems and Infrastructures, Muntean, M., & Brandas, C. (2007). Business Intelligence Support Systems and Infrastructures.
- Design and governance of collaborative business processes in industry 4.0, Schoenthaler, F., Augenstein, D., & Karle, T. (2015, July). Design and governance of collaborative business processes in industry 4.0. In Proceedings of the Workshop on Cross-organizational and Cross-company BPM (XOC-BPM) co-located with the 17th IEEE Conference on Business Informatics (CBI 2015) (pp. 1-8).
- Proposing a capability perspective on digital business models, Brenfnger, R., & Otto, B. (2015, July). Proposing a capability perspective on digital business models. In Business Informatics (CBI), 2015 IEEE 17th Conference on (Vol. 1, pp. 17-25). IEEE. Business models comprehensively describe the functioning of businesses in contemporary economic, technological, and societal environments. This paper focuses on the characteristics of digital business models from the perspective of capability research and develops a capability model for digital businesses. Following the design science research (DSR) methodology, multiple evaluation and design iterations were performed. Contributions to the design process came from IS/IT practice and the research base on business models and capabilities.
- Successful Customer Relationship Management: Why, ERP, Data Warehousing, Decision Support, and Metadata Matter, Davis, J., & Joyner, E. (2001). Successful Customer Relationship Management: Why, ERP, Data Warehousing, Decision Support, and Metadata Matter. In Customer Relationship Management (pp. 301-309). Vieweg+ Teubner Verlag, Wiesbaden. A CRM system is only as successful as the quality of data and data-management processes supporting it. Organizations planning wisely beyond the next millennium are thinking beyond process automation and are focused on getting better acquainted with customers to increase revenues and profits. Maintaining a sound metadata strategy as well as understanding the roles of ERP, decision support, and data warehousing systems is crucial for attaining this higher level of understanding.
- Introduction to Business Analytics, Business Intelligence, and Big Data Minitrack, Marjanovic, O., Ariyachandra, T., & Dinter, B. (2014, January). Introduction to Business Analytics, Business Intelligence, and Big Data Minitrack. In 2014 47th Hawaii International Conference on System Sciences (HICSS) (pp. 3727-3727). IEEE.
- Exploring the Underlying Relations between the Business Intelligence and Knowledge Management, Zarghamifard, M., & Behboudi, M. R. (2012). Exploring the Underlying Relations between the Business Intelligence and Knowledge Management. International Journal of Science and Engineering Investigations, 1(2), 31-35.
- A platform for market intelligence, De Man, D. (2012, October). A platform for market intelligence. In International Trade Forum (No. 4, p. 21). International Trade Centre