GROUP 1- IMPORTANCE OF DATA INTEGRITY.pdf

Topic in Computer data management explaining the importance of data integrity

1. IMPORTANCE
OF DATA
INTEGRITY IMPORTANCE
OF DATA
INTEGRITY DATA MANAGEMENT GROUP 1

2. WHAT IS DATA INTEGRITY? It refers to the accuracy, completeness, consistency, and validity of data.
It ensures reliable decision-making by maintaining trustworthy information.TYPES OF DATA INTEGRITY:
1. Physical Integrity
Protects data from damage or corruption due to external factors (e.g., power
outages, hardware failures).
2. Logical Integrity
Ensures data remains consistent and valid within databases and prevents
unauthorized changes.

3. Entity Integrity: Ensures each row in a table has a unique, non-null
primary key.
Referential Integrity: Maintains consistency between related tables
using foreign keys.
Domain Integrity: Enforces valid data types and values for each column
(e.g., ZIP codes).
User-Defined Integrity: Custom business rules for specific data usage
(e.g., requiring full customer names).
Four Aspects of Logical Integrity:

4. DATA INTEGRITY VS. DATA QUALITY Focuses on maintaining
data’s reliability,
completeness, and
protection from corruption.
Ensures data remains intact
during entry, transmission,
and storage.
Supports system recovery,
security, and compliance
Focuses on maintaining
data’s reliability,
completeness, and
protection from corruption.
Ensures data remains intact
during entry, transmission,
and storage.
Supports system recovery,
security, and compliance

5. DATA INTEGRITY BEST PRACTICES
Human error
System malfunctions
Unauthorized access
Lack of validation and testing
Poor governance
Identify Sources of Data Corruption:

6. DATA INTEGRITY BEST PRACTICES
Referential Integrity
Unique Constraint
Data Type Check
Range Check
Nullability
Check Constraint
Database-Level Integrity Checks:

7. DATA INTEGRITY BEST PRACTICES
Access Controls
Data Backups
Data Validation
Audits
Employee Training
Encryption
Business-Level Integrity Practices:

8. DATA INTEGRITY BEST PRACTICES
Human and machine factors
Lack of integration
Manual data entry
Missing audit trails
Legacy systems
Consequences of poor data integrity
Risk mitigation strategies
Business benefits
Data Integrity Challenges

9. THANK YOU!!