Updated March 8, 2023
Introduction to Data integrity
Data integrity deals with data maintenance. The term data integrity will assure that the data should be consistent and accurate into its entire life cycle. To design the correct data integrity life cycle model is a complex and critical task. In this various processes come into the picture like the designing phase, implementation phase, utilization of the machine or system like processing power, read or write data, storage, etc. To make sure that, the data integrity should be consistent or have the good quality of the data. We need to do the data quality checks as well. But in data integrity, data validation is mandatory before processing anything on the data level.
Types of Data integrity
When we are saying data integrity, we need to make sure that the data should be consistent and accurate even if it will flow under multiple processes. While processing it with the multiple processes, the data should be clearer and it will hold the same value or hold the meaningful data.
There are different types of data integrity. As per the project or application need, we need to select which type of data integrity technique we need to choose. The first type of data integrity is physical integrity. The second type of data integrity is logical integrity. The physical and logical integrity is nothing but a collection of the process. It also includes the method as well. It will also impose the data reliability in together the relational databases and ranked format.
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Physical data integrity
In physical integrity, it is a defence of the accuracy and completeness of the data. It will help to retrieved and stored. When natural disasters may come like the power goes down, hackers disrupt database working and functions, natural disasters strike or physical data integrity will compromise. In some cases, the host of other issues will not be able to process the applications programmers, data processing managers, system programmers, internal auditors, etc will help to obtain the accurate and the correct data. IN the Physical data integrity, generally, we are not using any automation way for the data integrity. We are majorly focused on physical assistance for validating the data. Due to which are able to achieve the physical data integrity. While doing the Physical integrity, it might happen that due to human error, we are not able to achieve physical data integrity. Hence we need to prefer logical data integrity or we need to use some automation to achieve data integrity.
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Logical data integrity
Logical data integrity will help to keep the data unaffected. We can use the logical data integrity in the different ways in the RDBMS or in the different relational databases. In the physical data integrity, there are lots of changes for the data inconsistency. But in the logical data integrity, there is less chance for the data errors. Here, we are getting the consistency and the value data. Hence, when are we getting a huge amount of data or when the incoming data frequency is to high then we need to use the logical data integrity. It will help to keep the data consistent and keep the data account even if it will process with the different data processes under the enter data process life cycle.
There are four different types of logical data integrity i.e.
- Entity data integrity
- Referential data integrity
- Domain data integrity
- User-defined data integrity
Entity data integrity
In logical data integrity, entity data integrity is based on the formation of the primary keys. It will help to identify the exclusive value points and help to identify the pieces of the data. It will also make sure that the data will not list multiple times (not more than the single iteration). There is no field value that should be null. It will deal with the relational system. It will store the data in terms of the table format. We can also link with the different entities and use them in different methods.
Referential data integrity
In the referential integrity, it will help to refer to the sequence of the processes that will make sure that the data is a store and it will use in a uniform way. The integrity rules will be implanted into the DB format. It will also ensure that the additions, deletions, appropriate changes on the data level. In the same defined rules, it will also include the constraints that will help to make sure that the data should precise, it will eliminate the data duplicate entry, prohibit the access of data (it will perform the action as and/or)where it will doesn’t apply it.
Domain integrity
In the domain of integrity, it will help to collect the number of procedures that will enforce the integrity and the correctness of every piece of the data. It will do the data check on the domain level. In the concept, the domain is the satisfactory values that will hold by the column level (it will contain the satisfactory values). It will also include the constraints. It will also include the other measures also that will limit the type, format, arrival, quantity of data, etc.
User-defined data integrity
The user-defined data integrity will include the list of constraints and the rules that would be formed by the client-side or end-user. It will help to create the rules in such a way that they will fit as per the need or the requirement. In some cases, the referential, domain integrity, entity, etc are not able to protect the data. Hence we need to define our own strategies and plan to protect the data. That’s why we are using user-defined data integrity.
Conclusion
We have seen the uncut concept of “data integrity” with the proper explanation. Data integrity is used to ensure that the data should be correct and consistent. The data should be consistent even if it will process through multiple processes. There are two main types of data integrity i.e. physical and logical integrity.
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