Overall, while all categories of data analytics are useful, the choice of approach depends on the specific needs of the organization and the presentation's goals. A data dashboard typically includes a combination of descriptive, diagnostic, and predictive analytics (Richardson, V 2023). Descriptive analytics provides a high-level view of key performance indicators, such as revenue, expenses, and profits. Diagnostic analytics can be used to understand why a particular metric is performing poorly or well, such as identifying the root cause of a sudden drop in sales. Predictive analytics can be used to forecast future trends and identify potential risks and opportunities. Descriptive analytics is best for presenting historical data, while prescriptive analytics provides recommendations for optimal decision-making. According to Catherine Cote, writer at Harvard School of Business, product managers can use data analytics to analyze markets, industries, and user data to improve their companies products (Cote, C 2021). Moreover, predictive analytics is used to make predictions about future trends or events and to answer questions such as what might happen in the future. Because of the use of historical data being used in tandem with industry trends I believe that prescriptive analytics is a great approach for management presentations. Prescriptive analytics uses data, algorithms, and machine learning techniques to provide recommendations for optimal decision making (Richardson, V 2023). It helps management identify the best courses of action to achieve their specific goals and business objectives; which can give management a competitive advantage by making data-driven decisions quickly and efficiently. Using product managers as an example prescriptive analytics can be used to determine the best price for a product based on historical sales data, competitor pricing, and other factors. By using this analysis, management can make an informed decision in their pricing strategies.