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

摘要

The heart and soul of any BusinessIntelligence suite is its ETL (Extraction Transformationand Loading) capability. Business Intelligence (BI)helps the organizations to take informed decisions withthe help of properly formulated, known and unknownfacts. Integrating data from multiple sources andtransform it into a holistic data view for analysis is thecore feature of any BI platform. There exists many toolsand technologies to facilitate ETL and Data Warehouseactivities. These tools vary a lot in terms of maturityand usability. ETL is expensive in terms of computingresources and time. A poorly designed ETL steps cantake the entire BI solution into a toss.In current scenario, the term ETL is getting diminishedand the term Data Integration Tool (DIT) is gettingmore popular and widespread. In this paper we willtreat both terms synonymously. In an ETL or ratherData integration effort, business processes and domainknowledge are vital. This research paper is doing ananalysis of the popular Data Integration tools with anemphasis on healthcare Data Warehouse domain.Healthcare industry is unique thus the data associatedwith it is much more unique than any other sector. Thisstudy is the primary step towards the end to enddevelopment of a healthcare business intelligence orClinical Business Intelligence model.