Data Mining

Business Understanding

In this step, the goals of the businesses are set, and the important factors that will help in achieving the goal are discovered.

Data Understanding

This step will collect the entire data and populate the data in the tool (if using any tool).

Data Preparation

This step involves selecting the appropriate data, cleaning, constructing attributes from data, integrating data from multiple databases.

Modeling

Selection of the data mining technique such as decision-tree, generate test design for evaluating the selected model, building models from the dataset, and assessing the built model with experts to discuss the result is done in this step.

Evaluation

This step will determine the degree to which the resulting model meets the business requirements. The model is reviewed for any mistakes or steps that should be repeated.

Deployment

In this step, a deployment plan is made. The strategy to monitor and maintain the data mining model results to check for its usefulness is formed. Final reports are also made, and a review of the whole process is done to check any mistake and see if any step is repeated.

Classification

used to retrieve important and relevant information about data and metadata.

Clustering

used to identify data that are like each other. This process helps to understand the differences and similarities between the data. 

Regression

used to identify and analyze the relationship between variables

Association Rules

used to help find the association between two or more Items. It discovers a hidden pattern in the data set.

Outer detection

used to observe data items in the dataset that do not match an expected pattern or expected behavior.

Sequential Patterns

used to discover or identify similar patterns or trends in transaction data for a certain period.

Prediction

used to combine other data mining techniques like trends, sequential patterns, clustering, classification, etc. It analyzes past events or instances in the right sequence for predicting a future event.