In the previous article, you learned the purpose of data mining, which is to help various organizations, including businesses in extracting meaningful information. We are ready to discuss “What are the steps in data mining?”
In the data mining process, each step does some tasks to make the mining process easier. We shall look into each one of them one by one.
Step 1: Data cleaning
The first step is to remove any inconsistencies or noises from the data. This is wants data to be of same standards and be consistent on that standard.
Step 2: Data Integration
If you have multiple sources data, then all the data sources must be combined.
Step 3: Data Selection
Since, there are huge amount of data it is not necessary to read all data for analysis, instead we can only select relevant data such as based on time period, area, department, categories, so on for analysis task.
Step 4: Data Transformation
The data is consolidated or transformed into suitable form for mining.
Step 5: Data Mining
In this important step we use intelligent methods including statistics to extract meaningful patterns from the data.
Step 6: Pattern Evaluation
The patterns extracted that represent some knowledge must be evaluated. There are many interesting measures to evaluate such knowledge.
Step 7: Knowledge Representation
The ultimate goal of data mining is to present the information to users. In the last step, visualization techniques are used to present the mined knowledge to its users.
Note that the first four steps – data cleaning, data integration, data selection and data transformation are to prepare data for mining.