Abstract
Modern business intelligence (BI) is currently shifting the focus from the corporate internal data to external fresh data, which can provide relevant contextual information for decision-making processes. Nowadays, most external data sources are available in the Web presented under different media such as blogs, news feeds, social networks, linked open data, data services, and so on. Selecting and transforming these data into actionable insights that can be integrated with corporate data warehouses are challenging issues that have concerned the BI community during the last decade. Big size, high dynamicity, high heterogeneity, text richness and low quality are some of the properties of these data that make their integration much harder than internal (mostly relational) data sources. In this lecture, we review the major opportunities, challenges, and enabling technologies to accomplish the integration of external and internal data. We also introduce some interesting use case to show how context-aware data can be integrated into corporate decision-making.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Horkoff, J., Barone, D., Jiang, L., Yu, E.S.K., Amyot, D., Borgida, A., Mylopoulos, J.: Strategic business modeling: representation and reasoning. Softw. Syst. Model. 13(3), 1015–1041 (2014)
Thompson, J.L., Martin, F.: Strategic management: Awareness & change. Cengage Learning EMEA (2010)
Meredith, R., O’Donnell, P.: A functional model of social media and its application to business intelligence. In: Proceedings of the 2010 Conference on Bridging the Socio-technical Gap in Decision Support Systems: Challenges for the Next Decade, Amsterdam, The Netherlands, pp. 129–140. IOS Press (2010)
Sarawagi, S.: Information extraction. Found. Trends Databases 1(3), 261–377 (2008)
Banko, M., Cafarella, M.J., Soderland, S., Broadhead, M., Etzioni, O.: Open information extraction for the web. IJCAI 7, 2670–2676 (2007)
Uren, V., Cimiano, P., Iria, J., Handschuh, S., Vargas-Vera, M., Motta, E., Ciravegna, F.: Semantic annotation for knowledge management: requirements and a survey of the state of the art. Web Semant. Sci. Serv. Agents World Wide Web 4(1), 14–28 (2006)
García-Moya, L., Kudama, S., Aramburu, M.J., Berlanga, R.: Storing and analysing voice of the market data in the corporate data warehouse. Inform. Syst. Front. 15(3), 331–349 (2013)
Aggarwal, C.C., Zhai, C.: Mining Text Data. Springer Science & Business Media, New York (2012)
Koudas, N., Sarawagi, S., Srivastava, D.: Record linkage: Similarity measures and algorithms. In: Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data, SIGMOD 2006, pp. 802–803. ACM, New York (2006)
Pavel, S., Euzenat, J.: Ontology matching: State of the art and future challenges. IEEE Trans. Knowl. Data Eng. 25(1), 158–176 (2013)
Pérez, J.M., Berlanga, R., Aramburu, M.J., Pedersen, T.B.: Integrating data warehouses with web data: a survey. IEEE Trans. Knowl. Data Eng. 20(7), 940–955 (2008)
Abelló, A., Romero, O., Pedersen, T.B., Berlanga, R., Nebot, V., Cabo, M.J.A., Simitsis, A.: Using semantic web technologies for exploratory OLAP: a survey. IEEE Trans. Knowl. Data Eng. 27(2), 571–588 (2015)
Bhide, M., Gupta, A., Gupta, R., Roy, P., Mohania, M.K., Ichhaporia, Z.: LIPTUS: associating structured and unstructured information in a banking environment. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, Beijing, China, June 12–14, 2007, pp. 915–924 (2007)
Bhide, M., Chakravarthy, V., Gupta, A., Gupta, H., Mohania, M.K., Puniyani, K., Roy, P., Roy, S., Sengar, V.S.: Enhanced business intelligence using EROCS. In: Proceedings of the 24th International Conference on Data Engineering, ICDE 2008, 7–12, April 2008, Cancún, México, pp. 1616–1619 (2008)
Baeza-Yates, R., Ribeiro-Neto, B., et al.: Modern Information Retrieval, vol. 463. ACM Press, New York (1999)
Pérez-Martínez, J.M., Berlanga, R., Aramburu, M.J., Pedersen, T.B.: Contextualizing data warehouses with documents. Decis. Support Syst. 45(1), 77–94 (2008)
Croft, B., Lafferty, J.: Language Modeling for Information Retrieval, vol. 13. Springer Science & Business Media, New York (2013)
Castellanos, M., Gupta, C., Wang, S., Dayal, U., Durazo, M.: A platform for situational awareness in operational BI. Decis. Support Syst. 52(4), 869–883 (2012)
Berlanga, R., García-Moya, L., Nebot, V., Aramburu, M.J., Sanz, I., Llidó, D.M.: SLOD-BI: an open data infrastructure for enabling social business intelligence. IJDWM 11(4), 1–28 (2015)
Bizer, C.: The emerging web of linked data. IEEE Intell. Syst. 24(5), 87–92 (2009)
Fernández, J.D., Llaves, A., Corcho, O.: Efficient RDF interchange (ERI) format for RDF data streams. In: Mika, P., et al. (eds.) ISWC 2014, Part II. LNCS, vol. 8797, pp. 244–259. Springer, Heidelberg (2014)
Balduini, M., Della Valle, E., Dell’Aglio, D., Tsytsarau, M., Palpanas, T., Confalonieri, C.: Social listening of city scale events using the streaming linked data framework. In: Alani, H., et al. (eds.) ISWC 2013, Part II. LNCS, vol. 8219, pp. 1–16. Springer, Heidelberg (2013)
Wang, H., Fan, W., Yu, P.S., Han, J.: Mining concept-drifting data streams using ensemble classifiers. In: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2003, pp. 226–235. ACM, New York (2003)
Gaber, M.M., Zaslavsky, A., Krishnaswamy, S.: Mining data streams: a review. SIGMOD Rec. 34(2), 18–26 (2005)
Calders, T., Dexters, N., Gillis, J.J.M., Goethals, B.: Mining frequent itemsets in a stream. Inf. Syst. 39, 233–255 (2014)
Nebot, V., Berlanga, R.: Towards analytical MD stars from linked data. In: KDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval, Rome, Italy, 21–24 October, 2014, pp. 117–125 (2014)
Gallinucci, E., Golfarelli, M., Rizzi, S.: Advanced topic modeling for social business intelligence. Inf. Syst. 53, 87–106 (2015)
Acknowledgements
This work has been funded by the Spanish Economy and Competitiveness Ministry (MINECO) with project contract TIN2014-55335-R.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Berlanga, R., Nebot, V. (2016). Context-Aware Business Intelligence. In: Zimányi, E., Abelló, A. (eds) Business Intelligence. eBISS 2015. Lecture Notes in Business Information Processing, vol 253. Springer, Cham. https://doi.org/10.1007/978-3-319-39243-1_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-39243-1_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-39242-4
Online ISBN: 978-3-319-39243-1
eBook Packages: Business and ManagementBusiness and Management (R0)