Data Conversion for Year 11

What is data conversion?

• Data conversion is the process of deleting unnecessary data.

• Data conversion is the process of transforming data from one format to another.

• Data conversion is the method of backing up data to prevent loss.

• Data conversion refers to the storage of data in a database.

Why is data conversion important in computing?

• Data conversion enables interoperability and ensures data integrity across different systems.

• Data conversion is irrelevant in modern computing.

• Data conversion is only necessary for large datasets.

• Data conversion slows down system performance.

Name two common formats for data conversion.

• CSV and JSON

• TXT and DOCX

• XML and HTML

• YAML and PDF

What is the difference between lossy and lossless conversion?

• Lossy conversion loses some data and quality, while lossless conversion retains all data and quality.

• Lossy conversion is faster than lossless conversion, regardless of data type.

• Lossy conversion retains all data and quality, while lossless conversion loses some data.

• Lossy conversion is used for text files, while lossless conversion is used for images.

How can data be converted from analog to digital?

• Data is converted from analog to digital by compressing the file.

• Data is converted from analog to digital by sampling, quantizing, and encoding the signal.

• Data is converted from analog to digital by amplifying the signal.

• Data is converted from analog to digital by filtering the noise.

What role does software play in data conversion?

• Software has no impact on data formats.

• Software plays a crucial role in automating and managing the transformation of data between different formats.

• Software is only used for data storage.

• Software is irrelevant in data processing.

Explain the term 'data migration'.

• Data migration refers to the backup of data in a cloud storage.

• Data migration is the process of transferring data from one system to another.

• Data migration is the analysis of data for business intelligence.

• Data migration is the process of deleting unnecessary data.

What are some challenges faced during data conversion?

• Challenges faced during data conversion include data loss, format incompatibility, errors in data mapping, and differences in data types and structures.

• Data conversion only involves changing file names.

• Data conversion is a straightforward process with no challenges.

• Data conversion always results in improved data quality.

How can data integrity be maintained during conversion?

• Skipping data validation steps

• Data integrity can be maintained by validating data, using reliable tools, accurate mapping, and thorough testing.

• Ignoring data formats during conversion

• Using outdated software tools

Give an example of a situation where data conversion is necessary.

• Data conversion is necessary when creating a new user account on a website.

• Data conversion is necessary when integrating customer data from multiple sources with different formats.

• Data conversion is necessary when sending emails to customers.

• Data conversion is necessary when backing up files to a cloud service.