Data Mining in CRM (Customer Relationship Management): Customer Relationship Management (CRM) is all about obtaining and holding Customers, also enhancing customer loyalty and implementing customer-oriented strategies. To get a decent relationship with the customer, a business organization needs to collect data and analyze the data. Data Mining Functionalities. It becomes an important research area as there is a huge amount of data available in most of the applications. Data Mining Functionalities For example, students who are weak in maths subject. These include: 1. Data mining functionalities are used to specify the kind of patterns to be found in data mining tasks. There are number of data mining functionalities. If you are curious about learning data science to be in the front of fast-paced technological advancements, check out upGrad & IIIT-B’s PG Diploma in Data Science. Data Mining Functionalities – Doesn’t matter in which order they are executed But: resulting rules are unnecessarily complex – It needs to remove redundant tests/rules. Education : Data mining benefits educators to access student data, predict achievement levels and find students or groups of students which need extra attention. Data Mining Functionalities - Free download as PDF File (.pdf), Text File (.txt) or view presentation slides online. Data mining tasks can be classified into two categories: descriptive and predictive. Data mining helps insurance companies to price their products profitable and promote new offers to their new or existing customers. Holistically data mining and functionalities find many applications from space science to retail marketing. Data mining functionalities are used to specify the kind of patterns to be found in data mining tasks. Data Mining is defined as the procedure of extracting information from huge sets of data. Data mining has an important place in today’s world. In general, data mining tasks can be classifi ed into two categories: descriptive and predictive. The data mining functionalities are used to specify kind of patterns which are to be identified in a data mining system. From rules to trees More difficult: transforming a rule set into a tree – Tree cannot easily express disjunction between rules Example: rules which test different attributes Data Mining Functionalities. Descriptive mining tasks characterize the general properties of the data in the database. Class Characterization and Discrimination In other words, we can say that data mining is mining knowledge from data. Predictive mining tasks perform inference on the current data in order to make predictions. This huge amount of data must be processed in order to extract useful information and knowledge, since they are not explicit.
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