We know that Data mining is becoming an increasingly important tool to transform data into information. To satisfy the same need we offer our customers a wide range of tools to convert data into information for marketing, surveillance, fraud detection and scientific discovery etc, Data mining takes place over 3 main steps:

• Pre-processing: The target set is first cleaned. Cleaning removes the observations with noise and missing data. The feature vectors are divided into two sets, the "training set" and the "test set". The training set is used to "train" the data mining algorithm(s), while the test set is used to verify the accuracy of any patterns found.
• Data mining: Data mining commonly involves four classes of tasks,

• Classification - Arranges the data into predefined groups. Clustering - Is like classification but the groups are not predefined, so the solution will try to group similar items together. Regression - Attempts to find a function which models the data with the least error. Association rule learning - Searches for relationships between variables.

  
  
• Results validation: The final step of knowledge discovery from data is to verify the patterns produced by the data mining algorithms occur in the wider data set.