IMPLEMENTATION OF MULTIDIMENSIONAL EXPRESSIONS (MDX) ON CUBE: A CASE STUDY OF BIRTH REGISTRATION DATA

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1 International Journal of Computer Engineering & Technology (IJCET) Volume 6, Issue 12, Dec 2015, pp , Article ID: IJCET_06_12_002 Available online at ISSN Print: and ISSN Online: IAEME Publication IMPLEMENTATION OF MULTIDIMENSIONAL EXPRESSIONS (MDX) ON CUBE: A CASE STUDY OF BIRTH REGISTRATION DATA Pushpal Desai Assistant Professor, M.Sc. (I.T.) Programme, Veer Narmad South Gujarat University ABSTRACT The structured query language (SQL) is used for various operations on database; a multidimensional expression (MDX) is query language for analysis service. The MDX can be effectively used to browse the cube. Brion Larson defined as MDX as programming language for OLAP Cube navigation [1]. Brion Larson explains that MDX is very important for analysis as it has feature of advanced mathematics and formulas. Furthermore, MDX also allows us to navigating through the dimensions and hierarchies of OLAP cube [1]. All these features are not part of T-SQL and hence it is very important for us to use MDX script for analysis purpose in data warehouse environment. In the previous research work, various operations on cube were shown using design mode [2] [3]. In the paper, different analytical scenarios and respective MDX queries are discussed on birth registration data cube. Cite this Article: Pushpal Desai. Implementation of Multidimensional Expressions (MDX) On Cube: A Case Study of Birth Registration Data. International Journal of Computer Engineering and Technology, 6(12), 2015, pp INTRODUCTION In our earlier research work, we discussed implementation of data cube for birth registration data of the city of Surat [2][3]. In the data cube, various dimensions like religion, zone, delivery method, delivery attention, year, parents eduction etc were used and birth data count and birth weight attributes were used as measures in the cube. Using these dimensions and measures of data cube, MDX queries are designed and executed for performing different analytical tasks. 9 editor@iaeme.com

2 Pushpal Desai 2. METHODOLOGY Considering common analytical needs of the organization, in this paper few MDX queries are designed and results are obtained. In the following section, various analytical needs and their MDX queries are given: MDX Query 1: Natural. ON COLUMNS FROM [BirthDatabase2015]) WHERE ([Deleivery Method Name].[Deleivery Method].&[3] ) MDX Query 2: Natural and Caesarean. Method].&[3], [Deleivery Method Name].[Deleivery Method].&[1] } ) ON COLUMNS FROM [BirthDatabase2015]) WHERE ([Deleivery Method Name].[Deleivery Method].CurrentMember) MDX Query 3: Natural and Caesarean and Delivery Attention as Institutional-Government. ON COLUMNS FROM ( SELECT ({[Deleivery Attention Master].[Delievery Attention].&[2] } ) ON COLUMNS FROM (SELECT ({[Deleivery Method Name][Deleivery Method].&[3], [Deleivery Method Name].[Deleivery Method].&[1] } ) ON COLUMNS FROM [BirthDatabase2015])) WHERE ([Deleivery Method Name].[Deleivery Method].CurrentMember, [Deleivery Attention Master].[Delievery Attention].&[2] ) MDX Query 4: Natural and Caesarean and Delivery Attention as Institutional-Private or Non Government. SELECT {[Measures] [Birth Data Count] } ON COLUMNS FROM (SELECT ({[Deleivery Attention Master].[Delievery Method].&[3], [Deleivery Method Name].[Deleivery Method].&[1] } ) ON COLUMNS FROM [BirthDatabase2015])) WHERE ([Deleivery Method Name].[Deleivery Method].CurrentMember, 10 editor@iaeme.com

3 Implementation of Multidimensional Expressions (MDX) On Cube: A Case Study of Birth Registration Data [Deleivery Attention Master].[Delievery Attention].&[3] ) MDX Query 5: Natural, Delivery Attention as Institutional-Private or Non Government, Religion as Hindu and Zone as Central ON COLUMNS FROM (SELECT ({[Zone Master].[ZoneName].&[2] } ) ON COLUMNS FROM (SELECT ({[New Religion Master].[Religion].&[4] } ) ON COLUMNS FROM [BirthDatabase2015])))) WHERE ([Deleivery Method Name].[Deleivery Method].&[3], [New Religion Master].[Religion].&[4], [Zone Master].[ZoneName].&[2] ) MDX Query 6: Natural, Delivery Attention as Institutional-Private or Non Government, Religion as Muslim and Zone as Central SELECT { [Measures].[Birth Data Count] } ON COLUMNS FROM (SELECT ({[Zone Master].[ZoneName].&[2] } ) ON COLUMNS FROM (SELECT ({[New Religion Master].[Religion].&[6] } ) ON COLUMNS FROM [BirthDatabase2015])))) WHERE ([Deleivery Method Name].[Deleivery Method].&[3], [New Religion Master].[Religion].&[6], [Zone Master].[ZoneName].&[2] ) MDX Query 7: Natural, Delivery Attention as Institutional-Private or Non Government, Religion as Hindu, Zone as South, West, North, East and Education Level as Graduate or Above. ON COLUMNS FROM (SELECT ({[New Education Master].[Education Level].&[1] } ) ON COLUMNS FROM ( SELECT ( { [Zone Master].[ZoneName].&[3], [Zone Master].[ZoneName].&[4], [Zone Master].[ZoneName].&[5], [Zone Master].[ZoneName].&[1] } ) ON COLUMNS FROM ( SELECT ( { [New Religion Master].[Religion].&[4] } ) 11 editor@iaeme.com

4 Pushpal Desai ON COLUMNS FROM [BirthDatabase2015]))))) WHERE ( [Deleivery Method Name].[Deleivery Method].&[3], [New Religion Master].[Religion].&[4], [Zone Master].[ZoneName].CurrentMember, [New Education Master].[Education Level].&[1] ) MDX Query 8: Natural, Delivery Attention as Institutional-Private or Non Government, Religion as Jain, Zone as South, West, North, East and Education Level as Graduate or Above. ON COLUMNS FROM (SELECT ({[New Education Master].[Education Level].&[1] } ) ON COLUMNS FROM ( SELECT ( { [Zone Master].[ZoneName].&[3], [Zone Master].[ZoneName].&[4], [Zone Master].[ZoneName].&[5], [Zone Master].[ZoneName].&[1] } ) ON COLUMNS FROM (SELECT ({[New Religion Master].[Religion].&[5] } ) ON COLUMNS FROM [BirthDatabase2015]))))) WHERE ([Deleivery Method Name].[Deleivery Method].&[3], [New Religion Master].[Religion].&[5], [Zone Master].[ZoneName].CurrentMember, [New Education Master].[Education Level].&[1] ) 3. RESULTS Based on discussed MDX queries, the results were obtained using SQL Server Analysis Services. The results were obtained considering various combinations of dimensions like Delivery Method, Delivery Attention, Zone, Religion, Education Level etc These MDX results are provided in the Table 1. Considering this as sample of MDX queries, organization can do further extend analysis of birth data by designing and executing more MDX queries. The Figure 1 and Figure 2 shows results obtained by executing MDX query 7 and MDX query 8. This preliminary work shows importance of MDX in data warehouse environment editor@iaeme.com

5 Implementation of Multidimensional Expressions (MDX) On Cube: A Case Study of Birth Registration Data Table 1 Result of MDX queries 1 to 8 No MDX Query Result 1 Natural. Birth Data Count: Birth Data Count: Natural and Caesarean. 4 Natural and Caesarean and Delivery Attention as Birth Data Count: Institutional-Government 4 Natural and Caesarean and Delivery Attention as Birth Data Count: Institutional-Private or Non Government 5 or Non Government, Religion as Hindu and Zone Birth Data Count: as Central 6 or Non Government, Religion as Muslim and Zone Birth Data Count: 5172 as Central 7 or Non Government, Religion as Hindu, Zone as Birth Data Count: South, West, North, East and Education Level as Graduate or Above. 8 or Non Government, Religion as Jain, Zone as South, West, North, East and Education Level as Graduate or Above. Birth Data Count: 396 Figure 1 Result of MDX query editor@iaeme.com

6 Pushpal Desai Figure 2 Result of MDX query 8 ACKNOWLEDGEMENTS AND LIMITATION All results are based on data of year 2000 to year 2009 provided by the municipal corporation for the research purpose only and results may vary if data warehousing concepts are implemented using OLTP systems of corporation. REFERENCES [1] Delivering Business Intelligence with Microsoft SQL Server 2008, Brion Larson [2] The Study on Data Warehouse and Data Mining for Birth Registration System of the Surat City, International Journal of Computer Applications, ISBN: ,Number 4 - Article 2, 2011, 1-5, Pushpal Desai & Apurva Desai [3] Knowledge Discovery from Birth Registration E-Governance Data using Data Mining, Indian Journal of Applied Research, Volume: 4 Issue: 9 September 2014 ISSN X, PUSHPAL DESAI [4] Pushpal Desai. Data Mining Prediction Using Data Mining Extensions (DMX): A Case Study on E-Governance Birth Registration Data Mining Model. International Journal of Advance Research in Engineering and Technology, 5(6), 2014, pp editor@iaeme.com