Top 5 Must-Know Data Mining Fundamentals

Data Mining is an essential component of Big Data technologies and Big Data analysis techniques. Generally, the term Data Mining refers to data analysis from different perspectives and made to turn these data into useful information, establishing relationships between data or by identifying patterns . This information can then be used by companies to increase revenues or reduce costs. They can also be used to better understand customers to develop better marketing strategies.

Data Mining is based on complex and sophisticated algorithms to segment the data and assess future probabilities. Data Mining is also known as Knowledge Discovery in Data (discovery of knowledge in the data).

4 types of relations

  • Classes
  • Clusters
  • Associations
  • Sequential patterns

The 5 major elements:

  • The extraction, transformation, and loading data on the Data Warehouse system.
  • Storage and management of data
  • Provide data access
  • Analyze data
  • Present data

Data Mining process in 5 steps

  • Collect data and load it into the data warehouse.
  • Store and manage data.
  • Determine how to organize data.
  • Sort data based on user results.
  • Share data as a chart or table.

6 levels of analysis

  • The artificial neural networks
  • Genetic algorithms
  • Decision trees
  • The method of the nearest neighbour
  • The induction rule
  • Data visualization

The 3 main properties of Data Mining

  • Automatic discovery of patterns
  • The prediction of likely outcomes
  • Creating actionable information
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