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Data mining consists of tasks like user interfacing, mining, security, performance, and data source. The following is a discussion on various tradeoffs of data mining [3–5, 14].

 ◦ User interface designAs discussed in the KDD process where discovered knowledge needs to be represented using good, accurate visualization. The user interface design issue addresses the interaction required within users and the systems, information rendering. This issue requires analysts, programmers to work on different conceptual levels.

 ◦ Mining methodologies issuesThis issue addresses the following sub-points:Algorithms to be usedError-free dataLess time complexityMetadata processing.

 ◦ Security issuesSecurity is a very important issue in data mining. Data collection, data processing requires maintaining the integrity, confidentiality of the data. Data mining systems deal with the private and sensitive information of the users and hence providing security to this data is a primary objective of this method.

 ◦ Performance issuesThere are many data mining applications existing in the market that are used in different sectors. These applications process a large volume of data and hence data mining algorithms; applications must process this data without compromising the performance of the system.

 ◦ Data source issuesData is collected from different sources, and it’s an incremental process. The number of data mining applications is increasing, which produces a large volume of data. It became a necessary task to store, process and categorized this large volume of data is a necessary task.