Y12 EC Unit 2 Week 2 PostQuiz

What is the primary goal of predictive data analytics?

• To identify current trends in data

• To make predictions about future trends based on historical data

• To store large volumes of data efficiently

• To enhance data security

Which of the following is an enterprise application of identifying patterns in data?

• Analyzing customer purchase behaviors to optimize inventory

• Conducting surveys for public opinion

• Comparing climate change data over decades

• Writing a research paper on ethical AI

Comparing datasets for an ethical issue can help in:

• Identifying biases in the data collection process

• Predicting future profits for a company

• Enhancing communication speeds

• Reducing storage costs

How does increased processing power impact data analytics?

• By enabling faster data collection

• By allowing more complex calculations and analyses

• By reducing the need for data storage

• By ensuring data integrity

What is a common social application of pattern recognition in data?

• Predicting voting behaviors during elections

• Enhancing server capacity

• Increasing website traffic

• Optimizing hardware performance

Which of the following best describes Online Analytical Processing (OLAP)?

• A process for storing data in a distributed system

• A method for querying and analyzing multidimensional data

The evolution of communication media impacts data analytics by:

• Enabling faster data transmission

• Reducing data redundancy

• Increasing computational costs

• Limiting data visualization options

What is one key ethical consideration when identifying patterns in data?

• Ensuring sufficient processing power

• Avoiding bias in data interpretation

• Increasing memory allocation

• Reducing the cost of software

Predictive analytics in healthcare often relies on:

• Identifying patterns in historical patient data

• Increasing storage capacity

• Enhancing graphic rendering capabilities

• Designing new medical devices

The evolution of storage/memory has impacted data analytics by:

• Allowing for the storage of larger datasets

• Replacing traditional processing methods

• Reducing the need for predictive analytics

• Limiting the accessibility of cloud-based solutions