The approaches and discussions given in this paper offer applicable solutions for a number of scenarios taking place in the contemporary world that are dealing with performance issues in development and use of analytical databases for the support of both tactical and strategic decision making. The paper introduces a novel method for expediting the development and use of analytical databases that combines columnar database technology with an approach based on denormalizing data tables for analysis and decision support. This method improves the feasibility and quality of tactical decision making by making critical information more readily available. It also improves the quality of longer term strategic decision making by widening the range of feasible queries against the vast amounts of available information. The advantages include the improvements in the performance of the ETL process (the most common time-consuming bottleneck in most implementations of data warehousing for quality decision support) and in the performance of the individual analytical queries. These improvements in the critical decision support infrastructure are achieved without resulting in insurmountable storage-size increase requirements. The efficiencies and advantages of the introduced approach are illustrated by showing the application in two relevant real-world cases.
['Nenad Jukic', 'Boris Jukic', 'Abhishek Sharma', 'Svetlozar Nestorov', 'Benjamin Korallus Arnold']
Expediting analytical databases with columnar approach