What are the three categories of business analytics?

What are the three categories of business analytics?

• A. Descriptive, evaluative, and predictive
• B. Descriptive, financial, and operational
• C. Descriptive, predictive, and prescriptive
• D. Descriptive, context-based, and goal-driven

Answer: (C)

The three categories of business analytics are correctly identified as descriptive, predictive, and prescriptive. Descriptive analytics focuses on summarizing historical data to understand what has happened in the past. This often involves using various statistical methods to analyze past performance and generate insights that can inform current business situations. For example, a company may use descriptive analytics to evaluate sales data from the previous year to identify trends and behaviors. Predictive analytics goes a step further by utilizing historical data and statistical algorithms to forecast future events or outcomes. This type of analysis seeks to identify patterns that can be used to predict future behaviors, enabling businesses to make proactive decisions. An example could be a retailer predicting next quarter’s sales based on past purchasing trends and external factors like seasonality. Prescriptive analytics takes the analysis a step further by recommending actions based on the data analyzed. It incorporates various techniques, such as optimization and simulation, to suggest how to handle potential future scenarios effectively. For instance, a logistics company might use prescriptive analytics to determine the best routes for delivery trucks based on real-time traffic data, cost considerations, and customer needs. The other choices provide combinations that do not fully capture the structured approach of business analytics. Descriptive and evaluative are not standard terms used in the

The three categories of business analytics are correctly identified as descriptive, predictive, and prescriptive.

Descriptive analytics focuses on summarizing historical data to understand what has happened in the past. This often involves using various statistical methods to analyze past performance and generate insights that can inform current business situations. For example, a company may use descriptive analytics to evaluate sales data from the previous year to identify trends and behaviors.

Predictive analytics goes a step further by utilizing historical data and statistical algorithms to forecast future events or outcomes. This type of analysis seeks to identify patterns that can be used to predict future behaviors, enabling businesses to make proactive decisions. An example could be a retailer predicting next quarter’s sales based on past purchasing trends and external factors like seasonality.

Prescriptive analytics takes the analysis a step further by recommending actions based on the data analyzed. It incorporates various techniques, such as optimization and simulation, to suggest how to handle potential future scenarios effectively. For instance, a logistics company might use prescriptive analytics to determine the best routes for delivery trucks based on real-time traffic data, cost considerations, and customer needs.

The other choices provide combinations that do not fully capture the structured approach of business analytics. Descriptive and evaluative are not standard terms used in the