A Survey on gap between SQL and DMQL
S. Poojita · 2014
An important motivation for the development of databases is proactive use of the information significantly improve the quality of their decision making and profitability of the organization through focused actions. Query languages like SQL and DMQL plays vital role in retrieving the data from different data sources. In this paper we compare existing data mining query languages, all extensions of the standard relational query language SQL, from this point of view: how flexible are they with respect to the tasks they can be used for, and how easily can those tasks be performed? We verify whether and how these languages can be used to perform three prototypical data mining tasks in the domain of association rule mining, Clustering and Classification. We also evaluated functional gap between the SQL and DMQL.