Exploring Business Intelligence Concepts

What is the primary purpose of data visualization?

• To make complex data accessible and understandable.

• To create artistic representations of data.

• To store data in a database.

• To perform complex mathematical calculations.

Name three common data visualization techniques.

• histograms

• heat maps

• bar charts, line graphs, pie charts

• scatter plots

What does ETL stand for in data processing?

• Extract, Transform, Load

• Extract, Transform, List

• Extract, Transform, Link

• Extract, Transfer, Load

Describe the main steps involved in the ETL process.

• Retrieve, Process, Export

• The main steps in the ETL process are Extract, Transform, and Load.

• Extract, Analyze, Load

• Collect, Transform, Store

What is the role of data cleaning in ETL?

• Data cleaning is only necessary for data storage.

• Data cleaning ensures data quality and reliability in the ETL process.

• Data cleaning is used to enhance data visualization.

• Data cleaning is a step that occurs after data analysis.

How does predictive analytics differ from descriptive analytics?

• Predictive analytics forecasts future events, whereas descriptive analytics summarizes past data.

• Descriptive analytics predicts future trends.

• Predictive analytics focuses on data visualization.

• Predictive analytics only analyzes historical data.

What is a common algorithm used in predictive analytics?

• Support Vector Machines

• Linear Regression

• Decision Trees

• K-Means Clustering

Explain the concept of regression analysis in predictive modeling.

• Regression analysis focuses solely on time series data.

• Regression analysis is a statistical method for modeling the relationship between a dependent variable and one or more independent variables to make predictions.

• Regression analysis is used only for categorical data.

• Regression analysis cannot be used for prediction purposes.

What are some tools commonly used for data visualization?

• Photoshop

• Microsoft Word

• AutoCAD

• Tableau, Power BI, Matplotlib, D3.js, Google Charts, QlikView, and Excel.

How can predictive analytics benefit business decision-making?

• Predictive analytics benefits business decision-making by enabling data-driven insights, enhancing forecasting accuracy, and facilitating proactive strategies.

• It eliminates all risks associated with business decisions.

• It guarantees 100% accurate predictions every time.

• It reduces the need for data analysis entirely.