In a world of big data, ensuring that your data collection and analysis systems are accurate and consistent is more important than ever. Too frequently we see big companies in the spotlight due to data breaches or for not prioritizing outputs that are thoroughly researched and evidence-based with accurate data.
This is why data integrity needs to be at the forefront of any business plan so that your reputation is not compromised. In this article, we explain what data integrity is, why it is important, and go through some methods on how you can maintain data integrity across your company.
Data Integrity – What is it?
Having data integrity means that that the data collected is consistent, accurate, and without big gaps. Safety and security are also a crucial part of data integrity as this is the extent to which your data complies with government regulations, such as GDPR. True data integrity can only be achieved with a well thought out set of rules and processes on how data will be collected and stored. Once this is in place, you can be confident of the integrity of your data even if you’re not going to be accessing it regularly.
Are there different types of data integrity?
Yes, now it is time to get into the bare bones of data integrity and how it is implemented. Let’s take a look at each different type in turn:
Physical integrity refers to the problems faced in correctly storing the data itself. This can be compromised by natural disasters, a cut to the power supply, hackers trying to attack your system, or multiple other physical interruptions that are frequently beyond your control. However, physical integrity can be upheld by methods such as investing in an uninterruptible power supply or other measures to protect the system against physical interruptions.
Physical integrity can also be compromised by human error. This can be mitigated through the use of error detecting algorithms that can be used to check for errors.
Logical integrity is concerned with ensuring that the data collected makes sense and involves putting systems and processes in place to make sure this happens at every step of data collection. Logical integrity is broken down into the following 4 areas:
- Referential integrity: referential integrity is a set of rules that are written into the structure of your database that only allow certain changes, deletions, or additions to be made to the data. These rules can ensure that it is impossible to enter repeated data and reject a data entry that is not accurate.
- Entity integrity: this refers to a set of primary keys that can identify data and ensure that there are no gaps left in a data table and that data isn’t repeated.
- Domain integrity: domain integrity refers to the accuracy of the data and can refer to the creation of a set of acceptable values that are embedded in the database so that unacceptable values in certain formats or amounts are not able to be entered.
- User-defined integrity: this isn’t always applicable, however, user-defined integrity, is used to fit a user’s specific needs and rules can be embedded into the database for this.
What puts data integrity at risk?
Even when physical and logical integrity are considered and plans put in place to uphold them, there is still room for error and there can still be risks to your data. These can include, but are not limited to, bugs and viruses that can attempt to corrupt or steal your data, human error, errors when data is transferred, or failures in computer hardware and servers that can put data at risk.
These factors can be mitigated through several proactive measures, including:
– Ensuring data is backed up regularly
– Running data validation regularly to check on data accuracy
– Restricting access to admin processes on the database so that changes can only be made by those who are trained to do so
– Investing in error detection software
– Maintaining an up-to-date data log so that you know exactly when data changes have been made.
Where to start with data integrity
We understand that all of this information might have given you a headache. Fortunately, there are experts, such as Claravine, that can ensure a lot of the systems required for data integrity are put in place for you so that you can trust in how your data is being collected and stored.
Using an integration platform for your data has many benefits, with all of your company’s data in one location and the ability for all departments to access this with measures in place so that you can standardize, govern and connect data across your teams. A worthy investment for both time management and data utilization.