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Strategic Management for Real-Time Business Intelligence

  • Conference paper

Part of the Lecture Notes in Business Information Processing book series (LNBIP,volume 154)

Abstract

Even though much research has been devoted on real-time data warehousing, most of it ignores business concerns that underlie all uses of such data. The complete Business Intelligence (BI) problem begins with modeling and analysis of business objectives and specifications, followed by a systematic derivation of real-time BI queries on warehouse data. In this position paper, we motivate the need for the development of a complete Real Time BI stack able to continuously evaluate and reason about strategic objectives. We argue that an integrated system, able to receive formal specifications of the organization’s strategic objectives and to transform them into a set of queries that are continuously evaluated against the warehouse, offers significant benefits. In this context, we propose the development of a set of real-time query answering mechanisms able to identify warehouse segments with temporal patterns of special interest, as well as novel techniques for mining warehouse regions that represent expected, or unexpected threats and opportunities. With such a vision in mind, we propose an architecture for such a framework, and discuss relevant challenges and research directions.

Keywords

  • Strategic Management
  • Data Warehouse
  • Market Segment
  • Business Intelligence
  • Data Cube

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Barone, D., Jiang, L., Amyot, D., Mylopoulos, J.: Composite indicators for business intelligence. In: Jeusfeld, M., Delcambre, L., Ling, T.-W. (eds.) ER 2011. LNCS, vol. 6998, pp. 448–458. Springer, Heidelberg (2011)

    CrossRef  Google Scholar 

  2. Chamoni, P., Stock, S.: Temporal structures in data warehousing. In: Mohania, M., Tjoa, A.M. (eds.) DaWaK 1999. LNCS, vol. 1676, pp. 353–358. Springer, Heidelberg (1999)

    Google Scholar 

  3. Chaudhuri, S., Dayal, U.: An overview of data warehousing and OLAP technology. ACM SIGMOD Record 26(1) (March 1997)

    Google Scholar 

  4. Chen, B., Ramakrishnan, R., Shavlik, J.W., Tamma, P.: Bellwether analysis: Searching for cost-effective query-defined predictors in large databases. ACM TKDD 3(1) (March 2009)

    Google Scholar 

  5. Chen, Y., Dong, G., Han, J., Wah, B.W., Wang, J.: Multi-dimensional regression analysis of time-series data streams. In: VLDB, vol. 02 (2002)

    Google Scholar 

  6. Codd, E.F., Codd, S.B., Salley, C.T.: Providing OLAP (on-line Analytical Processing) to User-analysts: An IT Mandate, vol. 32. Codd & Date, Inc. (1993)

    Google Scholar 

  7. Drucker, P.F.: The age of discontinuity: Guidelines to our changing society. Harper and Row, New York (1968)

    Google Scholar 

  8. Golfarelli, M.: A survey on temporal data warehousing. International Journal of Data Warehousing 5 (2009)

    Google Scholar 

  9. Gupta, C., Wang, S., Ari, I., Hao, M.: Chaos: A data stream analysis architecture for enterprise applications. In: CEC (2009)

    Google Scholar 

  10. Han, J., Chen, Y., Dong, G., Pei, J., Wah, B.W., Wang, J., Cai, Y.D.: Stream Cube: An Architecture for Multi-Dimensional Analysis of Data Streams. Distributed and Parallel Databases 18(2) (2005)

    Google Scholar 

  11. Jarke, M., Lenzerini, M., Vassiliou, Y., Vassiliadis, P.: Fundamentals of Data Warehouses. Springer (2003)

    Google Scholar 

  12. Jiang, L., Barone, D., Amyot, D., Mylopoulos, J.: Strategic models for business intelligence. In: Jeusfeld, M., Delcambre, L., Ling, T.-W. (eds.) ER 2011. LNCS, vol. 6998, pp. 429–439. Springer, Heidelberg (2011)

    CrossRef  Google Scholar 

  13. Karakasidis, A., Vassiliadis, P., Pitoura, E.: ETL queues for active data warehousing. In: IQIS 2005 (2005)

    Google Scholar 

  14. Lamb, R.: Competitive strategic management. Prentice-Hall, Englewood Cliffs (1984)

    Google Scholar 

  15. Li, X., Han, J.: Mining approximate top-k subspace anomalies in multi-dimensional time-series data. In: VLDB (2007)

    Google Scholar 

  16. Mendelzon, A.O., Vaisman, A.A.: Temporal Queries in OLAP. In: Proceedings of the 26th International Conference on Very Large Databases (2000)

    Google Scholar 

  17. Middelfart, M.: Improving business intelligence speed and quality through the ooda concept. In: DOLAP 2007 (2007)

    Google Scholar 

  18. Middelfart, M., Bach Pedersen, T.: The meta-morphing model used in TARGIT BI suite. In: De Troyer, O., Bauzer Medeiros, C., Billen, R., Hallot, P., Simitsis, A., Van Mingroot, H. (eds.) ER Workshops 2011. LNCS, vol. 6999, pp. 364–370. Springer, Heidelberg (2011)

    CrossRef  Google Scholar 

  19. Middelfart, M., Pedersen, T.B.: Implementing sentinels in the targit bi suite. In: ICDE (2011)

    Google Scholar 

  20. Nag, R., Hambrick, D.C.: What is strategic management, really? Inductive derivation of a consensus definition of the field. Strategic Management, 955 (2007)

    Google Scholar 

  21. Palpanas, T., Chowdhary, P., Mihaila, G., Pinel, F.: Integrated model-driven dashboard development. ISF 9(2-3) (July 2007)

    Google Scholar 

  22. Palpanas, T., Sidle, R., Cochrane, R., Pirahesh, H.: Incremental maintenance for non-distributive aggregate functions. In: VLDB (2002)

    Google Scholar 

  23. Polyzotis, N., Skiadopoulos, S., Vassiliadis, P., Simitsis, A., Frantzell, N.E.: Supporting Streaming Updates in an Active Data Warehouse. In: ICDE (2007)

    Google Scholar 

  24. Sarawagi, S., Agrawal, R., Megiddo, N.: Discovery-Driven Exploration of OLAP Data Cubes. In: Schek, H.-J., Saltor, F., Ramos, I., Alonso, G. (eds.) EDBT 1998. LNCS, vol. 1377, pp. 168–182. Springer, Heidelberg (1998)

    CrossRef  Google Scholar 

  25. Souza, V.E.S., Garrigós, I., Trujillo, J.: Monitoring Strategic Goals in Data Warehouses with Awareness Requirements. In: ACM Symposium on Applied Computing (2012)

    Google Scholar 

  26. Vassiliadis, P., Simitsis, A., Georgantas, P.: A generic and customizable framework for the design of ETL scenarios. Information Systems (2005)

    Google Scholar 

  27. Watson, H.J., Wixom, B.H., Hoffer, J.A., Anderson-Lehman, R., Reynolds, A.M.: Real-time business intelligence: Best practices at continental airlines. Information Systems Management 23(1) (2006)

    Google Scholar 

  28. Xi, R., Lin, N., Chen, Y.: Compression and aggregation for logistic regression analysis in data cubes. In: TKDE (2009)

    Google Scholar 

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Zoumpatianos, K., Palpanas, T., Mylopoulos, J. (2013). Strategic Management for Real-Time Business Intelligence. In: Castellanos, M., Dayal, U., Rundensteiner, E.A. (eds) Enabling Real-Time Business Intelligence. BIRTE 2012. Lecture Notes in Business Information Processing, vol 154. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39872-8_9

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  • DOI: https://doi.org/10.1007/978-3-642-39872-8_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39871-1

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