Understanding Storage and Data Validation - Quiz 2

What is primary storage?

• Cache memory used for temporary data

• Secondary storage like hard drives

• External storage devices such as USB drives

• Primary storage is the main memory of a computer, typically RAM.

Name one type of primary storage.

• Random Access Memory (RAM)

• Optical Drive

• Solid State Drive (SSD)

• Hard Disk Drive (HDD)

What is secondary storage?

• Secondary storage is non-volatile storage used for permanent data retention.

• Storage that loses data when power is off.

• A type of RAM used for quick access.

• Temporary storage for active data processing.

Give an example of secondary storage.

• Solid state drive (SSD)

• USB flash drive

• Hard disk drive (HDD)

• CD-ROM

What is data validation?

• Data validation is the method of analyzing data trends over time.

• Data validation is the process of verifying that input data is accurate, complete, and meets specified criteria.

• Data validation is the process of collecting data from various sources.

• Data validation ensures that data is stored in a database correctly.

Why is data validation important?

• Data validation is only necessary for large datasets.

• Data validation slows down the data entry process.

• Data validation is irrelevant for statistical analysis.

• Data validation is important to ensure data accuracy and integrity.

What is a method of data validation?

• Data encryption

• Input masks

• Data compression

• Data visualization

What are data integrity checks?

• Processes that only focus on data storage

• Techniques for data visualization

• Methods to delete unnecessary data

• Data integrity checks are processes that ensure the accuracy and consistency of data.

How do data integrity checks help?

• Data integrity checks help maintain accuracy and consistency of data.

• They increase the speed of data retrieval.

• Data integrity checks are used for data visualization.

• They help reduce the amount of data stored.

What is one type of error that data validation can catch?

• Incorrect data format

• Excessive data length

• Incorrect data types

• Missing data fields