Introduction to Business Analytics

What is the first step in the data-driven decision-making flow?

• Identify Decision Needs

• Data Preprocessing

• Data Analysis

• Data Collection

Which analytics technique focuses on summarizing and describing historical data?

• Prescriptive Analytics

• Descriptive Analytics

• Machine Learning

• Predictive Analytics

What does Prescriptive Analytics involve?

• Forecasting future outcomes

• Recommending actions for decision optimization

• Summarizing historical data

• Cleaning and preprocessing data

In which sector does business analytics assist in risk management and financial forecasting?

• Education

• Supply Chain Management

• Healthcare

• Finance

What is the role of business analytics in E-commerce and Retail?

• Inventory management and pricing optimization

• Talent acquisition and performance management

• Patient care optimization

• Policy formulation and program evaluation

How does business analytics contribute to government agencies in the public sector?

• Improving educational outcomes

• Forecasting disease outbreaks

• Optimizing public services and policy formulation

• Enhancing customer experiences

How does analytics contribute to predictive maintenance in manufacturing and service industries?

• By summarizing historical data

• By analyzing equipment data to predict when maintenance is needed

• By processing and analyzing small datasets

• By recommending actions for decision optimization

What is the purpose of the feedback loop in the data-driven decision-making flow?

• Presenting insights using data visualization

• Collecting feedback on decision outcomes and incorporating lessons learned

• Enabling stakeholders to interpret and understand data implications

• Identifying decision needs

In which sector is HR Analytics commonly used for talent acquisition and performance management?

• Finance

• Healthcare

• Human Resources

• E-commerce and Retail

What role does data preprocessing play in the data-driven decision-making flow?

• Identifying decision needs

• Recommending actions for decision optimization

• Presenting insights using data visualization

• Cleansing and preprocessing collected data to ensure accuracy