Subject Oriented Data Partitioning – A Proposed Data Warehousing Schema

Data warehouse is an inseparable part of modern business but the amount of data it stores is huge and growing so fast, the queries of the business leaders it processes have become very sophisticated as well. Data warehouse needs to response to those queries with high quality data having less response time but the major challenge for that is the scale of data and nature of the queries involved. It's very hard to access the required data set with minimum response time in data processing as the data warehouse needs to perform analytical operation on a large set of data analyzing sophisticated queries. This paper introduces a new data warehousing schema that constructs a multidimensional relation tree hierarchy, changing the traditional use of relational database, with partitioned database in its every level instead of any individual data. This schema allows data warehouse to partition and process a large data part by part in a small batch to minimize the response time and stores summarized data to increase data availability in query processing. Allowing easy and fast access to the required set of data, this schema improves the performance and the decision making ability of the data warehouse.