A Comparative Analysis of Data Integration and Business Intelligence Tools with an Emphasis on Healthcare Data

A Comparative Analysis of Data Integration and Business Intelligence Tools with an Emphasis on Healthcare Data

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2020 by IJETT Journal
Volume-68 Issue-9
Year of Publication : 2020
Authors : Joseph George, Dr. M.K Jeyakumar
DOI :  10.14445/22315381/IJETT-V68I9P202

Citation 

MLA Style: Joseph George, Dr. M.K Jeyakumar  "A Comparative Analysis of Data Integration and Business Intelligence Tools with an Emphasis on Healthcare Data" International Journal of Engineering Trends and Technology 68.9(2020):5-9. 

APA Style:Joseph George, Dr. M.K Jeyakumar. A Comparative Analysis of Data Integration and Business Intelligence Tools with an Emphasis on Healthcare Data  International Journal of Engineering Trends and Technology, 68(9),5-9.

Abstract
The heart and soul of any Business Intelligence suite is its ETL (Extraction Transformation and Loading) capability. Business Intelligence (BI) helps the organizations to take informed decisions with the help of properly formulated, known and unknown facts. Integrating data from multiple sources and transform it into a holistic data view for analysis is the core feature of any BI platform. There exists many tools and technologies to facilitate ETL and Data Warehouse activities. These tools vary a lot in terms of maturity and usability. ETL is expensive in terms of computing resources and time. A poorly designed ETL steps can take the entire BI solution into a toss.
In current scenario, the term ETL is getting diminished and the term Data Integration Tool (DIT) is getting more popular and widespread. In this paper we will treat both terms synonymously. In an ETL or rather Data integration effort, business processes and domain knowledge are vital. This research paper is doing an analysis of the popular Data Integration tools with an emphasis on healthcare Data Warehouse domain. Healthcare industry is unique thus the data associated with it is much more unique than any other sector. This study is the primary step towards the end to end development of a healthcare business intelligence or Clinical Business Intelligence model.

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Keywords
Data Integration Tools, ETL, Business Intelligence, Data Warehouse, Clinical Business Intelligence, Data Visualization, Data Mart