Data Integrity
Core ConceptsDefinition
Data integrity refers to the accuracy, consistency, and reliability of data throughout its lifecycle during storage, retrieval, and processing.
Detailed Description
In the context of ERP systems, data integrity ensures that the data entered into the system is accurate, consistent, and reliable. This is crucial for organizations to guarantee the correct functioning of business processes across various departments. Data integrity involves the implementation of processes and standards to safeguard data from being altered unintentionally or maliciously, ensuring that it remains an accurate reflection of real-world conditions. It encompasses various aspects such as data validation, checksums, access controls, and error detection and correction protocols.
Key Features
- Access and authentication controls
- Audit trails and transaction logs
- Checksums and hash functions
- Data redundancy and error correction
- Data validation rules
Common Modules
Data Management
Module that provides tools for data storage, retrieval, and validation, ensuring data integrity.
Security and Compliance
Module that manages access controls and compliance standards to maintain data integrity.
Examples
Data Integrity with Checksums
A basic example of implementing a checksum method to ensure data has not been altered.
def verify_data_integrity(data, checksum): return hash(data) == checksumPopular Implementations
Role-based Access Control (RBAC)
Implementation example focusing on restricting data access to authorized users, thereby maintaining integrity.