Data Science

Understanding the importance of data integrity

data integrity

It isn’t just data security practices that will be needed to keep the electronic and physical data of your company safe. Strong data integrity practices will need to be taken into account as well.

While many businesses are coming to understand the need for data security, few, if any, actually appreciate the importance of data integrity.

But in the days of GDPR and increasing privacy laws, the easiest way to end up on the wrong side of government regulation is to have inaccurate data. A simple mistake can cause everything from minor administrative headaches to significant fines and setbacks. After all, this is the era of big data, and it’s high time for businesses to learn how to keep their data safe and accurate.

In this article, we’ll discuss what data integrity is, the primary ways it can become damaged or rendered inaccurate, and the steps your business can take to help preserve business integrity.

What is data integrity?

In short, data integrity is a process that ensures a company’s data is kept consistent and accurate throughout its lifecycle.

Accurate data is highly important in helping a company’s planning and decision making, as well as, in many cases, a requirement by law. This is why it’s so important that companies understand and implement data integrity correctly.

All major industries, from urban planning to education to online share trading platforms to aviation to healthcare require data integrity simply in order to operate.

How can data become damaged or inaccurate?

There are many ways that data can become damaged or inaccurate. The fact that data is always being created, moved, transferred, updated, and altered means that there are numerous points where it can become damaged.

For instance, data can be damaged in transit, as it is transferred over a network or to a storage device. It can also become corrupted because of a computer hardware failure.

Data can also become a victim of a poorly configured computing system, such as new software or security programs, or from bad agents using malware, or it can become damaged as a result of simple human error.

In essence, accurate data gives the business a crystal clear look at itself (with all the details necessary for it to make improvements and compete), but there are also so many ways that this data can become damaged to the point that it’s literally realistic to assume that at some point it will be.

Data cleaning and maintenance can

When data is damaged, the decisions it informs become faulty, ineffective, or worse, damaging to the company. This is why accurate and well-implemented data acquisition tools and strategies are more business-critical than many companies realize.

What is data integrity composed of?

For data to be effective, key elements need to be in place that ensures its usefulness:

  • Accurately logged. Data should include the author, date, and time of creation. It should also include appropriate, explanatory notes.
  • Properly formatted and easy to read. Uniform formatting helps the data to be searched and utilized efficiently. Ease of readability helps it to be understood.
  • Logged as it happens. The longer data takes to be logged, the more likely it is to be forgotten or inaccurate.
  • Kept in its original format. As data is utilized for various purposes, it should always be kept in its original format, with copies being used for other means. If it is continually changed as it is utilized, its accuracy will become damaged.
  • Free from errors. Ensure that data follows strict protocols and is error-free. Data might be logged in different formats (digitally or on paper if in the field), so there will need to be tight controls in place.

How to preserve data integrity

In order to ensure data integrity, input must be validated in real-time. An example of this would be a website contact form flagging an invalid email. Ideally, you’d want to automate this as much as possible, using digital forms that only allow specific information or reviewing paper forms when and where they’re filled out.

Once the input has been validated, the data itself has to be thoroughly checked and validated also. The purpose of this stage is to confirm the data is safe, meaningful, and correct. You can automate this stage by using scripts that organize and filter through your data, allowing you to efficiently double-check the data’s integrity.

This process can be done throughout transfer as well – such as checking a copy is correct when a file is downloaded from the internet. Files can also be security tested to ensure that they aren’t part of a data breach strategy.

Once the two stages of validation are complete, having a data backup is essential. By having two (or more) copies of your data, the likelihood that it will be misplaced decreases significantly.

The easiest way to do this is to store copies on the cloud, by using a VPS server storage solution that offers automated backups so you don’t even have to think about it. It’s also essential that the backup includes all of the original raw data as it was initially recorded. This is because different elements of data can easily be replaced or recreated, but raw data itself cannot.

Access controls should be implemented to any data systems, with access granted only on a business need basis. Unauthorized or unnecessary data usage should be prohibited, as it only increases the likelihood of damage.

For example, accounting does not need to access tech support data. This level of access control should be extended to physical paper records, which should be locked and stored securely. This is extremely important for data security, as it is important that your access control extends to making sure users access your data on secure networks.

Finally, you want to maintain a clear and easily understandable audit trail that records access to and usage of your data. Just as a hotel records the names and dates of guests that arrive and leave, your database plainly shows who has accessed it, what they have accessed, and any other actions they’ve taken.

This, again, isn’t just part of a strong data integrity practice but will help in understanding any data security threats you’ve fallen victim to and allow you to make better security choices in the future.

Conclusion

In short, data integrity is vitally important because it can improve the traceability and recoverability of data to the original source. It also ensures that your business data can be kept more secure and accurate. There are so many factors that can alter your data from the day that it is first created to when it’s transferred to other systems to when it is

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