Knowledge discovery is the process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data. It involves several steps including data preparation, data mining, and interpretation of results to extract meaningful information that can inform decision-making.

Knowledge Discovery

Valid patterns

Novel patterns

Potentially useful patterns

Understandable patterns

Data Preparation

Data mining is the process of discovering patterns and insights from large datasets by using machine learning, statistics, and database systems. It enables organizations to transform raw data into meaningful information, aiding in decision-making and predictive analysis.

Data Mining

The interpretation of results involves analyzing data outcomes to draw meaningful conclusions and determine their implications within a specific context. This process requires critical thinking to assess the validity, reliability, and significance of findings, ensuring they align with the research objectives and contribute to broader knowledge or decision-making frameworks.

Interpretation Of Results

Meaningful Information

Decision-making is a cognitive process that involves selecting a course of action from multiple alternatives, often under conditions of uncertainty. It is influenced by various factors such as individual biases, available information, and the decision-making environment.

Concepts

Relevant Degrees

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