What is the term for the method of identifying valid and useful patterns in data using mathematical and statistical techniques?

The correct answer is Knowledge Discovery in Database (KDD). This term refers to the overarching process of discovering useful information from a collection of data. KDD encompasses several steps, including selecting the data, pre-processing it, transforming it, mining the data to identify patterns, and evaluating and interpreting the mined patterns for relevance and utility.

KDD is a comprehensive approach that goes beyond merely analyzing data; it highlights the systematic process involved in extracting meaningful insights and knowledge from large datasets using mathematical and statistical methods. This involves applying tools and techniques to detect patterns, anomalies, associations, or trends that can inform decision-making.

In contrast, the other options represent concepts related but distinctly different from KDD. Knowledge Management refers to the process of capturing, distributing, and effectively using knowledge within an organization. Data Mining Techniques is a part of the KDD process, specifically focusing on the extraction of patterns from data but lacking the broader context of the entire knowledge extraction process. Information Retrieval is concerned with finding relevant information from large volumes of text or data, often through search engines and databases, but does not encompass the full scope of analysis and transformation involved in KDD.