The correct answer is B. knowledge.
Knowledge Discovery in Databases (KDD) is a process that uses data mining and other techniques to extract knowledge from data. Knowledge can be defined as a justified true belief. It is a valuable asset that can be used to make better decisions, improve products and services, and understand the world around us.
Data is the raw material that KDD uses to extract knowledge. Data can be structured or unstructured. Structured data is data that is organized in a defined format, such as a table or a spreadsheet. Unstructured data is data that is not organized in a defined format, such as text, images, or videos.
Data mining is a process that uses statistical, mathematical, and machine learning techniques to extract patterns from data. Data mining can be used to find patterns in data that are not obvious to humans.
KDD is a multi-step process that includes the following steps:
- Data selection. This step involves selecting the data that will be used in the KDD process.
- Data preprocessing. This step involves cleaning and transforming the data so that it is ready for mining.
- Data mining. This step involves using data mining techniques to extract patterns from the data.
- Knowledge representation. This step involves representing the knowledge that has been extracted from the data in a way that is understandable by humans.
- Knowledge evaluation. This step involves evaluating the knowledge that has been extracted from the data to determine its accuracy and usefulness.
- Knowledge deployment. This step involves deploying the knowledge that has been extracted from the data to solve a problem or improve a process.
KDD is a powerful tool that can be used to extract knowledge from data. However, it is important to note that KDD is not a magic bullet. It is a complex process that requires careful planning and execution.