Data Life Cycle

Question 1

What is stage 1 of the Data Life Cycle?

Answer 1

Data collection

Question 2

What are the key features of Data Collection?

Answer 2

• Gather raw data from various sources using sensors, user activity data, etc
• Data must be accurate and relevant
• Some challenges include: data quality, ethical considerations, accuracy, etc

Question 3

What is stage 2 of the Data Life Cycle?

Answer 3

Data Storage

Question 4

What are the key features of Data Storage?

Answer 4

• Must securely hold active data in physical/cloud storage
• There are different types of storage: spreadsheets, databases, cloud storage
• Must ensure data is secure using encryption or access controls
• Must comply with DPA and GDPR

Question 5

What is stage 3 of the Data Life Cycle?

Answer 5

Data processing

Question 6

What are the key features of Data Processing?

Answer 6

• Transforms raw data into useable formats through data cleaning, organisation and anonymising
• This ensures data quality and standardisation
• Use tools like Python (Pandas)

Question 7

What is stage 4 of the Data Life Cycle?

Answer 7

Data Analysis

Question 8

What are the key features of Data Analysis?

Answer 8

• Applying statistical. machine learning or visualisation techniques to gain insights
• Can use descriptive, diagnostic, prescriptive and predictive analysis
• Can use tools like Python and SQL

Question 9

What is stage 5 of the Data Life Cycle?

Answer 9

Data Disposal

Question 10

What are the key features of Data Disposal?

Answer 10

• Securely deleting/archiving data that isn’t needed
• Methods include deletion, anonymisation and archiving
• Can be challenging to ensure data is permanently removed to prevent unauthorised access