Lesson 6: Data Security

Lesson Outcomes

By the end of this lesson, learners will be able to:

  • Define data security and explain its importance
  • Identify common data security threats
  • Describe methods used to protect data
  • Explain the role of data security in databases and RPA
  • Understand legal and ethical responsibilities related to data protection

Lesson Overview

In this lesson, we focus on data security — one of the most critical aspects of working with data.

If data is the “gold” of modern organisations, then data security is the vault, guards, and alarm system combined. Without it, everything else you’ve learned in this module becomes a risk.

1. What is Data Security?

Data security refers to the processes and measures used to:

  • Protect data from unauthorised access
  • Prevent data loss or corruption
  • Ensure data privacy and confidentiality

👉 It applies to:

  • Databases
  • Files
  • Systems
  • Networks

2. Why Data Security is Important

  • Protects sensitive information (e.g., personal data, financial data)
  • Prevents cyberattacks and breaches
  • Maintains trust with users and customers
  • Ensures compliance with laws and regulations

👉 Example:
If a company loses customer data, it can face legal penalties and loss of reputation.

3. Common Data Security Threats

  • Unauthorised access – hackers gaining access to systems
  • Malware and viruses – software designed to damage systems
  • Phishing attacks – tricking users into revealing sensitive information
  • Data breaches – exposure of confidential data
  • Insider threats – employees misusing access

4. Methods of Protecting Data

a) Encryption

  • Converts data into unreadable format

  • Only authorised users can decrypt it

b) Access Control

  • Limits who can view or modify data

  • Uses usernames, passwords, and permissions

c) Authentication

  • Verifies identity (e.g., passwords, biometrics, OTPs)

d) Backups

  • Copies of data stored securely

  • Used to recover data in case of loss

e) Firewalls and Security Software

  • Protect systems from external attacks

5. Data Security in Databases

Databases must:

  • Restrict access to authorised users
  • Protect stored data using encryption
  • Maintain data integrity
  • Track user activity (audit logs)

👉 Example:
Only authorised employees should access customer financial records.

6. Data Security in RPA

In automation:

  • Bots handle sensitive data

  • Security must be enforced to:

    • Prevent misuse

    • Protect credentials

    • Ensure safe data transfer

👉 If a bot is not secured, it can become a vulnerability instead of a solution.

7. Legal and Ethical Considerations

Organisations must:

  • Comply with data protection laws
  • Protect personal information
  • Use data responsibly

Key principles:

  • Privacy
  • Confidentiality
  • Accountability

👉 Just because you can access data doesn’t mean you should.

8. Best Practices for Data Security

  • Use strong passwords
  • Regularly update systems
  • Limit access to necessary users only
  • Monitor systems for suspicious activity
  • Train employees on security awareness

Lesson Summary

In this lesson, you learned that:

  • Data security protects information from unauthorised access and threats
  • There are various risks such as cyberattacks and data breaches
  • Security measures include encryption, access control, and backups
  • Data security is essential in both databases and RPA systems
  • Legal and ethical responsibilities must always be followed when handling data
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