Data Warehouse Technologien

[HRO06] Halevy, A. Y.; Rajaraman, A.; Ordille, J. J.: Data Integration: The

Teenage Years. In: Proceedings of the International Conference on

Very Large Databases (VLDB), S. 9–16, 2006.

[HRU96] Harinarayan, V.; Rajaraman, A.; Ullman, J. D.: Implementing Da-

ta Cubes Efficiently. In: Proceedings of the International Confe-

rence on Management of Data (SIGMOD), S. 205–216. Montreal,

Kanada, 1996.

[HS98] Hernández, M. A.; Stolfo, S. J.: Real-world data is dirty: Data

cleansing and the merge/purge problem. Data Mining and Know-

ledge Discovery, Band 2, Nr. 1, S. 9–37, Jan 1998.

[HTT09] Hey, T.; Tansley, S.; Tolle, K. (Hrsg.): The Fourth Paradigm: Data-

Intensive Scientific Discovery. Microsoft Research, 2009.

[HZN

+

10] Héman, S.; Zukowski, M.; Nes, N. J.; Sidirourgos, L.; Boncz, P.:

Positional Update Handling in Column Stores. In: Proceedings of

the International Conference on Management of Data (SIGMOD),

S. 543–554. ACM, New York, NY, USA, 2010.

[IBM12] IBM: IBM DB2 Database for Linux, UNIX and Windows – In-

formationszentrale. http://pic.dhe.ibm.com/infocenter/db2luw/

v9r7/index.jsp, 2012.

[Inm92] Inmon, W. H.: Building the Data Warehouse. John Wiley & Sons,

Inc., 1992.

[Inm96] Inmon, W. H.: Building the Data Warehouse. John Wiley & Sons,

Inc., 2. Auflage, 1996.

[Inm99] Inmon, W. H.: Building the Operational Data Store. John Wiley &

Sons, 2. Auflage, 1999.

[ISO08] ISO: Information technology – Database languages – SQL –. Nr.

ISO/IEC 9075:2008(E). ISO/EIC, Genf, Schweiz, 2008.

[Jar89] Jaro, M. A.: Advances in Record Linkage Methodology as Applied

to the 1985 Census of Tampa Florida. Journal of the American

Statistical Society, Band 84, Nr. 406, S. 414–420, Juni 1989.

[Jar95] Jaro, M. A.: Probabilistic Linkage of Large Public Health Data

Files. Statistics in Medicine, Band 14, Nr. 5-7, S. 491–498, 1995.

[JK84] Jarke, M.; Koch, J.: Query Optimization in Database Systems.

ACM Computing Surveys, Band 16, Nr. 2, S. 111–152, 1984.

326 Literaturverzeichnis