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FME Enabled ETL Processes for Spatial and Attribute Data Analysis
Author(s) -
Farhad Alam,
Sanjay Pachauri
Publication year - 2017
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2017914754
Subject(s) - computer science , information retrieval , data mining , database , data science
ETL is a type of data integration that refers to the three steps (extract, transform, and load) used to blend data from multiple sources. It's often used to build a data warehouse. During this process, data is taken (extracted) from a source system, converted (transformed) into a format that can be analyzed, and stored (loaded) into a data warehouse or other system. FME has a rich data model designed implement ETL. FME provides tremendous transformation functionality, resulting in output that can be much greater than the sum of the inputs, and allowing data to be transformed from one type to another. The current paper uses FME workbench and implement the concept of ETL using a case study where a private firm wants to integrate attribute and spatial information regarding its employee, filter the unnecessary information and finally implement business query regarding Monthly Travelling Allowance. The results establish ETL and FEM as interdisciplinary technological domain and backbone of the data warehouse architecture.

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