What is the primary goal of "customer churn prediction" in business analytics?
A. Retaining existing customers
B. Maximizing computational complexity
C. Minimizing data storage costs
D. Extracting actionable insights
In data science, what is "data visualization" used for in business analytics?
A. Collecting data from various sources
B. Displaying data in graphical form
C. Identifying patterns in data
D. Calculating data storage costs
What is the main purpose of "market segmentation" in data science for business?
A. To group products by category
B. To categorize customers by behavior
C. To personalize marketing strategies
D. To eliminate product data
In business analytics, what is the primary goal of "predictive maintenance"?
A. Minimizing data collection costs
B. Reducing data storage requirements
C. Forecasting equipment failures
D. Analyzing market trends
What is the primary objective of "cluster analysis" in business data science?
A. Identifying patterns in data
B. Creating randomized experiments
C. Optimizing marketing campaigns
D. Calculating data storage costs
What is the primary focus of "market basket analysis" in business data science?
A. Analyzing customer purchase patterns
B. Identifying the most popular items
C. Calculating data storage costs
D. Tracking employee performance
In business analytics, what does the term "data integration" refer to?
A. Combining data from multiple sources
B. Storing data in a single database
C. Reducing data complexity
D. Sharing data with competitors
What does the acronym "ROI" stand for in the context of business analytics?
A. Return on Investment
B. Rate of Online Interaction
C. Random Order of Information
D. Redundant Operations Inference
In data science for business, what is the primary goal of "time series forecasting"?
A. Predicting future values based on time
B. Analyzing data within a timeframe
C. Sorting data by time intervals
D. Estimating data storage requirements
What is the primary focus of "text analytics" in business data science?
A. Analyzing textual data for insights
B. Calculating numerical statistics
C. Visualizing data patterns
D. Conducting online surveys
Which term describes the process of extracting meaningful information from large datasets for decision-making in business?
A. Data Visualization
B. Data Collection
C. Data Storage
D. Data Mining
What is the primary objective of "data-driven decision-making" in business?
A. Relying solely on intuition
B. Using data to inform choices
C. Avoiding data analysis
D. Reducing data storage requirements
In business analytics, what does the term "churn rate" represent?
A. The rate at which data is lost
B. The rate at which customers leave
C. The rate of data storage growth
D. The rate of data visualization
What is the primary purpose of "data warehousing" in business analytics?
A. Storing data for the long term
B. Extracting insights from data
C. Analyzing data in real-time
D. Managing data privacy
In the context of business analytics, what is the main goal of "data preprocessing"?
A. Making data analysis more complex
B. Preparing data for analysis
C. Reducing data storage costs
D. Increasing data collection
What is the primary goal of using data science in business analytics?
A. Increasing data privacy
B. Maximizing computational complexity
C. Minimizing data storage costs
D. Extracting actionable insights
In the context of business, what does the term "predictive modeling" refer to?
A. Anticipating future trends
B. Reviewing past performance
C. Assessing current market conditions
D. Estimating data storage requirements
What is the main purpose of "customer segmentation" in data science for business?
A. To group customers by age
B. To categorize customers by location
C. To personalize marketing strategies
D. To eliminate customer data
In data science, what is the term for using historical data to understand patterns and make informed decisions in business?
A. Descriptive Analytics
B. Predictive Analytics
C. Prescriptive Analytics
D. Diagnostic Analytics
What is the primary goal of "A/B testing" in business analytics?
A. Identifying differences in data
B. Creating randomized experiments
C. Optimizing marketing campaigns
D. Calculating data storage costs
