Maintaining Data Integrity: Types & Database Guide
- Data Integrity is Foundational: It’s the critical principle for ensuring data accuracy and consistency throughout its entire lifecycle within any system, especially databases.
- Mitigates Risks: Effectively maintaining data integrity safeguards against unintended data changes stemming from hardware failures, human error, or malicious intent.
- Six Core Steps: Essential practices for ensuring integrity include robust access controls, meticulous input/data validation, duplicate removal, consistent data backups, and thorough audit trails.
- Two Main Types: Data integrity is broadly categorized into Logical Integrity (concerning data rationality and correctness via constraints like Entity, Referential, Domain, and User-defined rules) and Physical Integrity (protecting data from external factors and storage issues).
Data integrity refers to ‘maintaining and assuring the accuracy and consistency of data over its entire life-cycle and is a critical aspect to the design, implementation, and usage of any system that stores, processes, or retrieves data. Any unintended changes to data as a result of a storage, retrieval, or processing operation, including malicious intent, unexpected hardware failure, and human error, are a failure of data integrity.
Today, we are looking at data integrity from a database point of view, as developers have various options for guaranteeing the integrity of data stored in the database.
Understanding of data integrity
Data integrity is imposed within a system at its design stage through the use of standard rules and procedures, and is maintained through the use of error checking and validation routines.
Having a single, well-controlled, and well-defined data-integrity system increases:
- Stability: One centralised system performs all data integrity operations.
- Performance: All data integrity operations are performed in the same tier as the consistency model.
- Re-usability: All applications benefit from a single centralised data integrity system.
- Maintainability: One centralised system for all data integrity administration.
Furthermore, you can minimise or eliminate the risks and ensure data integrity by following these simple six steps:
- Access controls.
- Validate input.
- Validate data.
- Remove duplicate data.
- Backup data.
- Always keep an audit trail.
Databases act as a crucial backbone that forms how a company’s data is stored and utilised. There are many Database Management Systems to choose from, allowing businesses to compare data points and query large data sets. Some popular options are: Oracle Database, Microsoft SQL Server, MySQL, PostgreSQL, and IBM Db2.
In a database application, you maintain data integrity by using constraints, defining the rules to which the operations (updating, deleting, inserting, etc) have to be performed to maintain data integrity. Ensuring that the data in the tables that the application manipulates conforms to the appropriate business rules. A business rule specifies a condition or relationship that must always be true or must always be false. The database administrator or application developer determines these business rules.
Type of data integrity
Data integrity is applied in all database models and can be divided into two main overlapping categories: physical and logical data integrity. Let us start by looking at the concept of logical data integrity.
Logical integrity
Logical integrity concerns with the rationality and correctness of data, given a particular context present within the relational database. Challenges to logical data integrity include software bugs, design flaws, and human error. Logical integrity constraints can be categorised into four subtypes:
- Entity integrity: No two rows can be the same; each record should be uniquely identified from others. This can be done with the help of the concept “primary key”. These are assigned in each table, so each entry of the table is uniquely identified. The value of the key mustn’t be NULL.
- Referential integrity: Maintaining data consistency between tables. When two or more tables have a relationship, we have to ensure that the foreign key value matches the primary key value at all times. Concerns the concept of the “foreign key”.
- Domain integrity: The validity of entries for a given column. The common ways to input and read this data are. The range of acceptable values.
- User-defined integrity: Apply business rules to the database that aren’t covered by any of the other three data integrity types.
Physical integrity
The domain of physical integrity relates to the protection of data as it is stored, used, and moved between apps. So it deals with protecting data against external factors, such as natural calamities, power outages, or hackers. Moreover, human faults, storage attrition, and several other problems can also make it unmanageable for data operators to obtain information from a database.
Well-designed databases incorporate the above principles in such a way that when you change data, the database itself prevents you from doing anything that might compromise the integrity of the data. So, it de facto becomes the responsibility of the database to ensure data integrity.
Want to know more about how Pinnaql can help your organisation to achieve and maintain data integrity throughout the entire database life cycle? Schedule your appointment today!
Data quality driven by technology is not merely a technical necessity but a fundamental pillar for business success in the modern era. By understanding the core dimensions of quality and strategically leveraging popular technology services, organizations can ensure the reliability of their data, empower better decision-making, and secure a crucial competitive advantage in an increasingly data-driven world.
- Astera. 2024. What is Data Integrity in a Database? Why Do You Need It?
- Fotra. 2018. What is Data Integrity? Definition, Types & Tips
At Pinnaql, we follow rigorous sourcing standards to ensure our content is accurate and up-to-date. We rely on trusted primary sources, including peer-reviewed research, academic institutions, and leading organizations. Our commitment is to provide reliable information you can trust. Notice an error? Reach out to us here.
