|

Enterprise Data Warehouse Design Method using SAP Net Weaver Business Warehouse

Authors: Tonoyan S.A., Vysochanskiy V.A. Published: 12.08.2016
Published in issue: #4(109)/2016  
DOI: 10.18698/0236-3933-2016-4-33-48

 
Category: Informatics, Computer Engineering and Control | Chapter: Computing Systems and their Elements  
Keywords: data warehouse, SAP, multidimensional data model, star-schema, OLAP, OLTP, info-cube, aggregation, LSA

Data warehouse is an informational system optimized to store large amounts of data and create analytical reports for decision support. Principles of classic data warehouse architecture cannot be applied for enterprise data warehouses (EDW) based on key performance indicators (KPI). In this article we offer a methodology that takes into account the KPI, we review and justify the enterprise data warehouse design technique using SAP NetWeaver Business Warehouse. Our step by step guide to data warehouse design features SAP LSA (Layered Scalable Architecture) standard. It consists of 7 layers, each serving the particular purpose of EDW functionality. LSA is flexible; it can be easily modified to fit various kinds of business processes. We provide a practical example of an EDW design for customs department of an oil and gas company.

References

[1] Baldin A.V., Tonoyan S. A., Eliseev D.V. Analysis of temporal data storage redundancy by means of RDBMS. Jelektr. nauchno-tekh. izd. "Inzhenernyy zhurnal: nauka i innovacii" [El. Sc.-Tech. Publ. "Eng. J.: Science and Innovation"], 2014, iss. 4. DOI: 10.18698/2308-6033-2014-4-1273 Available at: http://engjournal.ru/eng/catalog/it/hidden/1273.html

[2] Tonoyan S.A., Saraev D.V. Temporal database models and their properties. Jelektr. nauch-no-tekh. izd. "Inzhenernyy zhurnal: nauka i innovacii" [El. Sc.-Tech. Publ. "Eng. J.: Science and Innovation"], 2014, iss. 12. DOI: 10.18698/2308-6033-2014-12-1333 Available at: http://engjournal.ru/eng/catalog/it/hidden/1333.html

[3] Haupt Juergen. LSA. SAP NetWeaver, RIG BI EMEA, 2009. 43 p.

[4] Ballard C., Herreman D., Schau D., Bell R., Kim E., Valencic A. Data modeling technigues for data warehousing. International Technical Support Organization, IBM, 1998. 216 p.

[5] Baldin A.V., Tonoyan S.A., Eliseev D.V. Query language to mivar representation of relational databases, containing information archive from previous human resources systems. Jelektr. nauchno-tekh. izd. "Inzhenernyy zhurnal: nauka i innovacii" [El. Sc.-Tech. Publ. "Eng. J.: Science and Innovation"], 2013, iss. 11. DOI: 10.18698/2308-6033-2013-11-1053 Available at: http://engjournal.ru/eng/catalog/it/hidden/1053.html

[6] Patel B., Palekar A., Shiralkar Sh. SAP Net Weaver Business Warehouse (BW) 7. Bonn: Galileo Press, 2008. 689 p.

[7] Paklin N.B., Oreshkov V.I. Biznes analitika: ot dannykh k znaniyam [Business intelligence; From data to knowledge]. St. Petersburg, Piter Publ., 2013. 704 p.

[8] Barsegyan A.A. Analiz dannykh i protsessov [Analysis of data and processes]. St. Petersburg, BKhV-Peterburg Publ., 2009. 512 p.

[9] Chernen’kiy V.M., Tolochko S.I. Information system analysis and the definition of a notion of information system of prompt decision support. Vestn. Mosk. Gos. Tekh. Univ. im. N.E. Baumana, Priborostr., Spetsvyp no. 5 [Herald of the Bauman Moscow State Tech. Univ., Instrum. Eng., Spec. Issue no. 5], 2011, pp. 69-80 (in Russ.).

[10] Vinogradova M.V., Igushev E.G. Principles of data structure organization with random access and fast insert and delete operation. Jelektr. nauchno-tekh. izd. "Inzhenernyy zhurnal; nauka i innovacii" [El. Sc.-Tech. Publ. "Eng. J.: Science and Innovation"], 2012, iss. 3. DOI: 10.18698/2308-6033-2012-3-101 Available at: http://engjournal.ru/eng/catalog/it/asu/101.html

[11] Sarka D., Lah M., Jerkic G. Exam 70-463: Implementing a data warehouse with Microsoft SQL server 2012 Microsoft. Microsoft Press, 2013.

[12] Sperley E. Planning, building, and implementation (Enterprise data warehouse). Prentice Hall, 1999.