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Data Management

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Database Partitioning

JOHN OWENS

West Florida University

Data Management

March 18, 2014

Data partitioning is a tool that can help manage the day-to-day needs of an organization. Each organization has unique values that drive business. All organizations have policies and processes that are influenced by their environment and industry. The use of data partitioning can help productivity by recognizing the need to categorize data to tailor unique needs. This approach does require some effort. To transition to a new database approach, organizations need to assess the pros and cons of a database transition. The scale of an organization’s database may be the one factor that drives an adoption of this approach.
Data partitioning has been developed to address issues that traditional database queries have created. One main problem that partitioning was created to solve is the performance of database queries. According to Alsultanny (2010), “System performance is one of the problems where a significant amount of query processing time is spent on full scans of large relational tables. Partitioning of the vertical or horizontal partitioning or a combination of both is a reliable way of solving the problem” (p.273). By separating queries into either horizontal or vertical processes, the user can avoid delays and strains on a database. This saves time which can be used to improve the productivity an organization has towards their day-to-day operations.
Large-scale databases receive the most benefits from partitioning. Data partitioning can be customized to make frequent data more accessible. According to Wu (2001), “if a subset supports a large number of high-frequency rules, the weight of the subset should also be higher. The goal in this article is to extract the high frequency rules in the partitioned subsets. The high frequency rules are taken as the

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