It is no longer news that data serve as the basic utility for many businesses. In this time and age, it is even more of greater influence on businesses. Now, it is one thing for a company to lean into the usage of data and another thing to operate with data integrity.

Definition Of Data Integrity

Anything precision, reliability and validity in terms of information and data processing is what we call data integrity. Simply put, data is said to have integrity when it has reusability factor. It is original, uniform and is properly stored.

There are more than a few reasons to ensure that your data has integrity. Data integrity serves a lot of purpose in data input and output. Some of the things you stand to benefit from your data integrity are, it makes reusability of data possible and it provides easy accessibility and of course, helps to secure the correctness of information.

To prevent data integrity risk, you should build your system of organization in order to foster data integrity. There are things individuals can do to ensure the accuracy and reliability of data. The bigger task falls on whether the system of an organization is set up to favor data integrity.

There Are Various Things An Organization Must Consider Putting In Place. Some Of These Elements Are:

Maintain backup and recovery procedure

For you to successfully recover your data, you need to have put in place a certain back up procedure in place. Anyone familiar with the processes of data management knows this.

No one ever prays for sudden data loss. But, what we are not going to do is pretend that it does not happen. So, you must prepare adequately to ensure that when there is a possibility of data loss, recovery is just as possible.

Have a functional management system

There are a few things that can contend with a data quality management procedure when it comes to data protection. There is no pressing need to find out these other things. But, there is a need to build a management system for your organization too. This is capable of keeping the integrity of your data intact.

In building quality management system for your organization, you can omit other things save standard operating procedures. Doing this systematically helps to control the process of things in your organization.

Physical and logical systems need equal protection

There should be provision in all serious organizations for protecting both the physical system and logical system. In doing this, there comes a guarantee of data credibility.

There may not be a need to consider the damage that the protection of just the logical system can do. If there is no need to delve into the damage that only protecting the physical system can do. Because, whether or not it is a consensus, studies indicates that both systems are equally integral. Organizations need to zealously protect this system as they both help in maintaining data integrity.

Train data experts

Of course, not all organizations have the luxury to embark on this journey. But, if your organization is able, do not shy away from training people. Train people the best ways to engage the basic data processing procedures.

Proper training of users gives them leverage and insight to using the system to the advantage of the organization. You already know what lack or inadequate training is set to do.

Upgrade and validate the systems to be used

All computer systems to be used by in-house workers for data processing must from time to time be upgraded. Upgrade must be to the standard that the organization feels is best for that time. There is a need to validate these systems because they help to provide evidence that has been put into documentation.

In validating the system, know that you do not get the best form by limiting the work to what some amateurs do. Also, not by limiting to what in – house workers are able to come up with. You only get the best of service when you give vendors that are professionals in validating data.

Follow a software development cycle

Here is another very important thing to do if you must reduce data integrity risk. Reliability and validity of data do not just happen by chance or wishes but by putting in conscious effort. One effort an organization would never regret putting for data integrity is following a software development cycle.

All the computers or systems of an organization must follow a development cycle. This prevents the organization from being caught lagging behind in areas that should help data integrity.

Implement an audit trail

For what it is worth, data integrity deserves to have something as serious as an audit trail. It will become the testimony of your organization.

What an audit trail does is not so simple. For clear perspective, it helps to provide security for the system or computer put into use. . It also helps to automatically provide basic information about an entity. Also, helps to give information that range from name, date, time of data entries, changes, and deletions among other things.

The audit trail is also very responsible for the provision of necessary data ownership. It ensures that data become something that you can trust. It also helps to change data overtime and ensure data never get deleted.

Implement error detection software

Sometimes, no matter how much care a worker gives to data processing, there is no escaping data errors. The best way to then counter this error is to build a system or software that helps to quickly detect errors. This software gives the workers hints on corrections to make. For every errors you make, there is a machine that easily detects and guides correction.

In the same vein, the implementation of the error detection software helps to give data integrity it requires. When the data is accurate at all times, the use of this software inspires trust in anyone that is set to go through the data processing.

Joydeep SinghaGrowth Expert
Founder at AskDataEntry – India’s leading online virtual administration services provider for businesses and individuals. He is a seasoned marketing professional who is an expert in digital marketing and entrepreneurship.
Published On: September 14th, 2020 / Categories: Data Processing / Tags: , , /

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