What type of models are designed to discover patterns and extract insights from data using algorithmic techniques?

The identification of analytical models as those designed to discover patterns and extract insights from data using algorithmic techniques is correct due to their focus on data analysis and interpretation. Analytical models leverage various algorithms and methodologies to scrutinize data, helping to reveal trends, correlations, and insights that may not be immediately obvious. This approach enables businesses and researchers to make data-driven decisions and forecasts.

In the realm of cognitive project management for AI, analytical models play a critical role in facilitating understanding through the examination of complex datasets, which can include anything from sales patterns to user behaviors. Such models are often a bridge between raw data and actionable insights that guide strategic planning and operations.

Other types of models, while they have their own specific purposes, do not solely focus on the extraction of insights from data in the same broad manner as analytical models. Predictive models are primarily concerned with forecasts and future outcomes based on historical data, statistical models focus more on understanding data distributions and relationships, and descriptive models aim to summarize or explain characteristics of the collected data without necessarily delving into deeper insights.