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Comparative Study of Data Warehouse Modeling Techniques


Affiliations
1 Department of Computer Science, Institute of Statistical Studies and Research, Cairo University, Egypt
2 Faculty of Graduate Studies for Statistical Research, Cairo University, Egypt
     

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The continuous increase in data volume and data sources leads to an urgent need for analyzing this data. Hence the importance of designing a data warehouse model corresponds to the needs of companies and it’s considered as a key element in most of the data Analysis Systems. There are two main approaches in building the DW. The first is the Top-Down approach or the enterprise model for Bill Inmon and the second approach to Kimball which called Bottom-Up approach or the dimensional model. Each one of these approaches is widely used in building DW with some differences in the design. This paper highlights the difference between the two approaches and proposes recommendations for selecting the proper design.

Keywords

Data Warehouse, Top-Down, Bottom-Up, OLTP, OLAP and Data Mart.
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  • Comparative Study of Data Warehouse Modeling Techniques

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Authors

Atef Raslan
Department of Computer Science, Institute of Statistical Studies and Research, Cairo University, Egypt
Ahmad Saleh
Faculty of Graduate Studies for Statistical Research, Cairo University, Egypt

Abstract


The continuous increase in data volume and data sources leads to an urgent need for analyzing this data. Hence the importance of designing a data warehouse model corresponds to the needs of companies and it’s considered as a key element in most of the data Analysis Systems. There are two main approaches in building the DW. The first is the Top-Down approach or the enterprise model for Bill Inmon and the second approach to Kimball which called Bottom-Up approach or the dimensional model. Each one of these approaches is widely used in building DW with some differences in the design. This paper highlights the difference between the two approaches and proposes recommendations for selecting the proper design.

Keywords


Data Warehouse, Top-Down, Bottom-Up, OLTP, OLAP and Data Mart.

References