Which of the following analytical methods is commonly utilized in the "Perform Data Analysis" phase?

The analytical method commonly utilized in the "Perform Data Analysis" phase is machine learning models. These models enable analysts to identify patterns, make predictions, and derive insights from large datasets. By applying algorithms and statistical techniques, machine learning can uncover complex relationships within data that may not be immediately apparent through traditional analysis methods.

In the context of the "Perform Data Analysis" phase, leveraging machine learning models allows for a more automated and efficient approach to data processing and analysis. Analysts can utilize these models to enhance decision-making processes, optimize operations, and provide valuable forecasts based on historical data.

The other options, while relevant in different contexts, do not align directly with the typical objectives and techniques used during the data analysis phase. Qualitative research focuses on non-numerical data and often involves gathering insights through interviews or observations, making it less suitable for systematic data analysis compared to quantitative methods. Supplier negotiations pertain to procurement and supply chain processes and do not involve data analysis. Process mapping is a technique for visualizing workflows but does not primarily focus on the statistical analysis of data.