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Using Databases in Decisions Systems for Businesses

Received: 5 September 2016     Accepted: 20 October 2016     Published: 21 November 2016
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Abstract

The paper presents the usage of databases that store business data into a warehouse star model that permits to create queries using SQL language and business intelligence tools. This kind of model allow to the decision maker to create complex reports and graphs based on the columns from the dimension tables and measures from fact tables, that can be the base for creating alternatives and scenarious acording to the economical indicators. Building alternatives and scenarious is an elaborate task and must have a background in existing data structured in databases that have a special structure of dimensions and fact tables. This data warehouse star model allow complex analyses such as rollup, drill down, slice and dice through the dimensions and fact tables by using special tools such as online analythical processes and complex queries based on views and snapshots. To create simulation envolves changing strategic economical indicators and keeping restrains on others so they reflect reality and the business environment. The business environments require analyses on large amount of data, big data and necessitate advanced tools to query through numerous criterias and also to create different realistic scenarious that allow choosing one option, so the business manager can use the right tool to gain economic advantage.

Published in International Journal of Data Science and Analysis (Volume 2, Issue 2)
DOI 10.11648/j.ijdsa.20160202.11
Page(s) 15-20
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Business Intelligence Tools, Datawarehouse Star Model, SQL Queries and Reports, System Support Decisions, Analytical Tools and Management Decision

References
[1] Daniel J. Power, “Examples of decision support systems (DSS) aiding business decision-making”, http://searchbusinessanalytics.techtarget.com/tutorial/How-decision-support-systems-DSS-can-help-business-decision-making, 2015;
[2] Chang L, “Database Technologies for Decision Support System”, https://blogs.msdn.microsoft.com/csliu/2010/02/05/database-technologies-for-decision-support-system/, 2016;
[3] Gupta, Jatinder N. D., Thomas M. Harris, “Decision Support Systems for Small Business”, Journal of Systems Management, 2015;
[4] Muller-Boling, Detlef, Susanne Kirchhoff, “Expert Systems for Decision Support in Business Start-Ups.”, Journal of Small Business Management, 2015;
[5] Ramon Barquin, “Data warehousing: building the foundation”, http://searchdatamanagement.techtarget.com/, 2014;
[6] Surajit Chaudhuri, Umeshwar Dayal, Venkatesh Ganti, “Database Technology for Decision Support Systems”, IEEE Computer Society Press Los Alamitos, CA, USA, 2014;
[7] URI: http://searchcio.techtarget.com/definition/decision-support-system
[8] URI: http://www.dictionary.com/browse/decision-support-database
[9] URI:http://www.waterencyclopedia.com/Da-En/Data-Databases-and-Decision-Support-Systems.html
[10] URI: https://blogs.msdn.microsoft.com/database-technologies-for-decision-support-system/
Cite This Article
  • APA Style

    Dănut-Octavian Simion. (2016). Using Databases in Decisions Systems for Businesses. International Journal of Data Science and Analysis, 2(2), 15-20. https://doi.org/10.11648/j.ijdsa.20160202.11

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    ACS Style

    Dănut-Octavian Simion. Using Databases in Decisions Systems for Businesses. Int. J. Data Sci. Anal. 2016, 2(2), 15-20. doi: 10.11648/j.ijdsa.20160202.11

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    AMA Style

    Dănut-Octavian Simion. Using Databases in Decisions Systems for Businesses. Int J Data Sci Anal. 2016;2(2):15-20. doi: 10.11648/j.ijdsa.20160202.11

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  • @article{10.11648/j.ijdsa.20160202.11,
      author = {Dănut-Octavian Simion},
      title = {Using Databases in Decisions Systems for Businesses},
      journal = {International Journal of Data Science and Analysis},
      volume = {2},
      number = {2},
      pages = {15-20},
      doi = {10.11648/j.ijdsa.20160202.11},
      url = {https://doi.org/10.11648/j.ijdsa.20160202.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20160202.11},
      abstract = {The paper presents the usage of databases that store business data into a warehouse star model that permits to create queries using SQL language and business intelligence tools. This kind of model allow to the decision maker to create complex reports and graphs based on the columns from the dimension tables and measures from fact tables, that can be the base for creating alternatives and scenarious acording to the economical indicators. Building alternatives and scenarious is an elaborate task and must have a background in existing data structured in databases that have a special structure of dimensions and fact tables. This data warehouse star model allow complex analyses such as rollup, drill down, slice and dice through the dimensions and fact tables by using special tools such as online analythical processes and complex queries based on views and snapshots. To create simulation envolves changing strategic economical indicators and keeping restrains on others so they reflect reality and the business environment. The business environments require analyses on large amount of data, big data and necessitate advanced tools to query through numerous criterias and also to create different realistic scenarious that allow choosing one option, so the business manager can use the right tool to gain economic advantage.},
     year = {2016}
    }
    

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    AB  - The paper presents the usage of databases that store business data into a warehouse star model that permits to create queries using SQL language and business intelligence tools. This kind of model allow to the decision maker to create complex reports and graphs based on the columns from the dimension tables and measures from fact tables, that can be the base for creating alternatives and scenarious acording to the economical indicators. Building alternatives and scenarious is an elaborate task and must have a background in existing data structured in databases that have a special structure of dimensions and fact tables. This data warehouse star model allow complex analyses such as rollup, drill down, slice and dice through the dimensions and fact tables by using special tools such as online analythical processes and complex queries based on views and snapshots. To create simulation envolves changing strategic economical indicators and keeping restrains on others so they reflect reality and the business environment. The business environments require analyses on large amount of data, big data and necessitate advanced tools to query through numerous criterias and also to create different realistic scenarious that allow choosing one option, so the business manager can use the right tool to gain economic advantage.
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