1. Home
  2. BI
  3. Analytics
  4. Data, Text, and Web Mining
  5. Data Mining

By: Pascal PERRY


Data Mining Functions & Features

Data mininguses statistical analysis, artificial intelligence, and machine learning technologies to identify patterns that could not be found by manual analysis alone. Data mining covers the exploration and analysis of data, in great quantities, withthe purpose of discoveringpatternsor rules, which are meaningful.. Data Mining Functions & Features are an important module of the comprehensive BI RFP Template.

The BI RFP template with Data Mining Functions & Features for BI is a Microsoft Excel spreadsheet (.xlsx) featuring a total of 1955 decision criteria. The BI RFP template allows you to quickly and easily prepare the business, functional, and technical requirements sections of the solicitation package you'll send to BI software vendors. It ensures for:

  • complete response from each BI software vendor
  • deep and accurate evaluation of submitted BI proposals
  • impartial side-by-side comparison of BI solutions evaluated
  • rational and documented selection of the best matching BI system

The BI software comparison report can save you up to 90% of the time you would have otherwise spent comparing all the BI solutions from scratch.

The Data Mining Functions & Features comprise the following elements:

  • Data Mining Data Access

    Functionality covered Data capturing solution with multiple types of data, languages, and protocols support;Accesses data in remote databases;Accesses data held in ODBC-compliant database;Accesses data in flat files, SAS data sets, Microsoft Excel, IBM Visual Warehouse, and Oracle Express;Accesses web site data;Uses various data cleansing options to remove or replace invalid data and automatically fill in missing values;. Data Mining Data Access, Data Mining Functions & Features
  • Data Manipulation and Cleansing

    Major modules include Partitions data into training, test, and validation datasets;Works with complete record and field operations, including field filtering, naming, derivation, re-categorization, and value replacement;Records can be selected according to multiple criteria;Records selection, sampling, merging, and concatenating, sorting, aggregation. and balancing;Randomized sampling;Creates union, intersection, or complement of datasets;. Data Manipulation and Cleansing, Data Mining Functions & Features
  • Data Sampling

    Modules include Simple random;Stratified;Weighted;Cluster;Systematic;First N;. Data Sampling, Data Mining Functions & Features
  • Modeling

    Major modules covered Mines data in database where it resides within data modeling functionality;Use IBM DB2 Enterprise decision trees, regression, association, and demographic clustering techniques;Use Oracle 10g naïve Bayes and adaptive Bayes networks and SVM;Uses predictive and classification techniques;Browses the importance of the predictors decision trees and rule induction techniques, including CHAID, exhaustive CHAID, QUEST, and C&RT;Browses and interactively creates splits in decision trees;. Modeling, Data Mining Functions & Features

TEC Advisor can save you up to 90% of the time you would have otherwise spent figuring out on your own which BI solution is the best for your needs.

Compare Now!
Functions and Features