The video tutorial explains predictive analytics, an approach to forecasting future events using statistical data and modeling. It contrasts predictive analytics with descriptive and prescriptive analytics, highlighting its role as a middle ground. The tutorial discusses tools like machine learning and methodologies such as decision trees and regression analysis. It explores the application of predictive analytics in project management, particularly in planning and risk management, with a case study on Deloitte's five-stage process. Predictive analytics is shown to be valuable across various industries, including finance, marketing, and weather forecasting.

What is the primary goal of predictive analytics?

• To gather data in real-time

• To ensure certainty in decision-making

• To predict future outcomes

• To describe past events

Which of the following is NOT a methodology used in predictive analytics?

• Regression analysis

• Decision trees

• Descriptive statistics

• Neural networks

How does machine learning contribute to predictive analytics?

• By replacing traditional modeling

• By providing real-time data analysis

• By enhancing prediction accuracy

• By eliminating the need for data

In project management, predictive analytics is primarily used for:

• Budget estimation

• Project planning

• Team management

• Client communication

What is a key benefit of using predictive analytics in project scheduling?

• It reduces project costs

• It guarantees project success

• It provides real-time updates

• It eliminates all risks

Which company uses a five-stage risk management process involving predictive analytics?

• PwC

• Accenture

• Deloitte

• McKinsey

What is the final step in Deloitte's risk management process using predictive analytics?

• Reporting findings and recommendations

• Conducting interviews

• Document review

• Risk review