Suggestive Local Engine for SQL Developer: SLED

Abstract

Information Technology (IT) industry recruits junior staff on regular basis. Most of the applications use databases to store or access the data. Structure Query Language (SQL) is used to communicate with database middleware. An expensive SQL statement may engage the data centers for longer time forcing the organizations to sellout high cost for data storage and maintenance. A tool is required for training the junior developers. This study proposes a Suggestive Local Engine for SQL Developer (SLED). It develops a warehouse using the optimized SQL statements collected from reputed software firms or expert team. This study uses the concept of data marts to grouped the data and frequent pattern search algorithm to calculate frequencies and support of patterns of SQLstatements. This system suggests the developers based on the common patterns of SQL statements used by those experts. It also warns the developers if their writing pattern maps to the outlier statement. This system helps all the junior developers in an organization and graduates in colleges or universities to practice with suggestions. Keywords: Suggestive engine optimized SQL, Data Warehouse