DESIGN, IMPLEMENTATION, AND ASSESSMENT OF INNOVATIVE DATA WAREHOUSING; EXTRACT, TRANSFORMATION, AND LOAD(ETL); AND ONLINE ANALYTICAL PROCESSING(OLAP) IN BI

 


DESIGN, IMPLEMENTATION, AND ASSESSMENT OF INNOVATIVE DATA WAREHOUSING; EXTRACT, TRANSFORMATION, AND LOAD(ETL); AND ONLINE ANALYTICAL PROCESSING(OLAP) IN BI

Ramesh Venkatakrishnan

Final Year Doctoral Student, Colorado Technical University, Colorado, USA

ABSTRACT

The effectiveness of a Business Intelligence System is hugely dependent on these three fundamental components, 1) Data Acquisition (ETL), 2) Data Storage (Data Warehouse), and 3) Data Analytics (OLAP). The predominant challenges with these fundamental components are Data Volume, Data Variety, Data Integration, Complex Analytics, Constant Business changes, Lack of skill sets, Compliance, Security, Data Quality, and Computing requirements. There is no comprehensive documentation that talks about guidelines for ETL, Data Warehouse and OLAP to include the recent trends such as Data Latency (to provide real-time data), BI flexibility (to accommodate changes with the explosion of data) and SelfService BI. This research paper attempts to fill this gap by analyzing existing scholarly articles in the last three to five years to compile guidelines for effective design, implementation, and assessment of DW, ETL, and OLAP in BI.

KEYWORDS

Business Intelligence, ETL, DW, OLAP, design implementation and assessment

Full Text: https://aircconline.com/ijdms/V12N3/12320ijdms01.pdf

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