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HDSS Data Cleaning and Integration Using SAS Business Intelligence Tool


Affiliations
1 Department of Advanced Software and Computing Technology, India
2 IGNOU-I2IT Centre of Excellence for Advanced Education and Research, India
 

HDSS's (Health and Demographic and Surveillance Systems) are typically structured around subjects within the DSA (Demographic Surveillance Area). These subjects have both a conceptual and a logistical rationale. Major subject areas are: birth, death, in-migration, outmigration and delivery. Field workers collect HDSS data in various points of time and feed the data into computer systems manually. Further data analysis takes place. To have a concise view about major elements data cleaning and integration are required. Due to many dimensions and large volume of data, integration is becoming a challenging issue. Researcher performs data cleaning, transformation and integration manually. Which is a time consuming task? The current paper highlights the use of Business intelligence tools (SAS) for HDSS data integration. The experiment starts with Vadu-HDSS site (which is a member of INDEPTH NETWORK, Ghana), Pune, and Maharashtra. The current paper addresses the complexities in the HDSS data Integration, implementation, advantages and results.

Keywords

HDSS, DSA, iSHARE, Business Intelligence, Data Integration Studio, Data Repository
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Abstract Views: 192

PDF Views: 80




  • HDSS Data Cleaning and Integration Using SAS Business Intelligence Tool

Abstract Views: 192  |  PDF Views: 80

Authors

Venkatanaveen Dasari
Department of Advanced Software and Computing Technology, India
S. S. Suresh
IGNOU-I2IT Centre of Excellence for Advanced Education and Research, India

Abstract


HDSS's (Health and Demographic and Surveillance Systems) are typically structured around subjects within the DSA (Demographic Surveillance Area). These subjects have both a conceptual and a logistical rationale. Major subject areas are: birth, death, in-migration, outmigration and delivery. Field workers collect HDSS data in various points of time and feed the data into computer systems manually. Further data analysis takes place. To have a concise view about major elements data cleaning and integration are required. Due to many dimensions and large volume of data, integration is becoming a challenging issue. Researcher performs data cleaning, transformation and integration manually. Which is a time consuming task? The current paper highlights the use of Business intelligence tools (SAS) for HDSS data integration. The experiment starts with Vadu-HDSS site (which is a member of INDEPTH NETWORK, Ghana), Pune, and Maharashtra. The current paper addresses the complexities in the HDSS data Integration, implementation, advantages and results.

Keywords


HDSS, DSA, iSHARE, Business Intelligence, Data Integration Studio, Data Repository



DOI: https://doi.org/10.17697/ibmrd%2F2013%2Fv2i1%2F52215