Why Hadoop security protects sensitive data - See It in Action

Why Hadoop Security Protects Sensitive Data

📖 Scenario: You work in a company that stores lots of customer information using Hadoop. Your manager wants you to understand why Hadoop security is important to keep this sensitive data safe.

🎯 Goal: You will create a simple Python dictionary to represent sensitive data, set a security level, filter data based on security, and finally display the protected data.

📋 What You'll Learn

Create a dictionary called customer_data with exact entries for three customers and their sensitive info

Create a variable called security_level set to the string 'high'

Use a dictionary comprehension to create a new dictionary protected_data that only includes customers if security_level is 'high'

Print the protected_data dictionary

💡 Why This Matters

🌍 Real World

Companies use Hadoop to store large amounts of sensitive data like customer information. Protecting this data is critical to prevent leaks and unauthorized access.

💼 Career

Understanding how to protect sensitive data with security settings is important for data engineers and data scientists working with big data platforms like Hadoop.

1

Create the sensitive data dictionary

Create a dictionary called customer_data with these exact entries: 'Alice': 'SSN12345', 'Bob': 'SSN67890', 'Charlie': 'SSN54321'

Hadoop

# Create the customer_data dictionary with exact entries
# Your code here

Need a hint?

Use curly braces to create a dictionary with keys as names and values as sensitive info.

2

Set the security level

Create a variable called security_level and set it to the string 'high'

Hadoop

customer_data = {'Alice': 'SSN12345', 'Bob': 'SSN67890', 'Charlie': 'SSN54321'}
# Set the security_level variable to 'high'
# Your code here

Need a hint?

Assign the string 'high' to the variable security_level.

3

Filter data based on security level

Use a dictionary comprehension to create a new dictionary called protected_data that includes all entries from customer_data only if security_level is 'high'

Hadoop

customer_data = {'Alice': 'SSN12345', 'Bob': 'SSN67890', 'Charlie': 'SSN54321'}
security_level = 'high'
# Create protected_data dictionary using dictionary comprehension
# Your code here

Need a hint?

Use a dictionary comprehension with for name, info in customer_data.items() and an if condition checking security_level == 'high'.

4

Display the protected data

Print the protected_data dictionary to show the filtered sensitive data

Hadoop

customer_data = {'Alice': 'SSN12345', 'Bob': 'SSN67890', 'Charlie': 'SSN54321'}
security_level = 'high'
protected_data = {name: info for name, info in customer_data.items() if security_level == 'high'}
# Print the protected_data dictionary
# Your code here

Need a hint?

Use print(protected_data) to display the dictionary.