Information is becoming more and more critical in our data-driven world. However, when your currency is data, you need to know that it’s got your back. So how can you ensure you follow the right path with your data? Two words: data integrity.
Gartner’s Data Quality Market Survey found that in 2017, insufficient data cost businesses around 15 million dollars. So if poor information can do that to a business, just think what high-quality, good data can do.
Let’s Talk Data Integrity: What is it?
When we talk about a person with integrity, we speak about honesty, virtue, and purity. They have a reliable reputation, one that is consistent. Your data can, and should, have similar characteristics. We aren’t only talking about a state of being and an entire process involving how you maintain and manage your database.
When we look at a business’s data integrity, we’re looking at the big picture. Most people assume that we mean data security, and while the topic does involve protection, it’s about more than that. Data integrity looks at how complete and accurate your data is. You need to know that your information is reliable, consistent, and secure.
Business data must always be consistent. Making decisions in business has inherent risk; if you’re relying on data to make those decisions, you need to know it’s reliable. Unfortunately, nearly 50% of respondents to an IDC survey confessed that they didn’t feel secure in their data quality; that makes every decision a roll of the die.
There are many ways data integrity takes shape, and it comes in many types. There are six main types: entity integrity, domain integrity, referential integrity, and user-defined integrity are a few. However, physical integrity and logical integrity are the two most critical forms.
Physical integrity refers to how your data is stored and accessed, keeping it safe from a data breach. Logical integrity is how you protect your data from human errors.
A final area of data integrity regards compliance. Your business must meet regulatory standards, such as GDPR (General Data Protection Regulation). Data integrity is vital for meeting these standards, which helps your company avoid liability issues.
The Importance of Data Integrity
A company that makes data-driven decisions needs to know the information it’s working from is accurate. Your business decisions are sounder and more likely to pay off when you avoid bad or outdated data.
Data integrity ensures that your data continues to perform for you. Your employees need that flow of information for their work to remain steady; the data has to be available to them when needed. Without a consistent input of data, your data stream may become erratic. That could disrupt your business’s day-to-day operations.
A lack of proper security protocols is dangerous for your company. If your data and data analytics becomes compromised, your business suffers. You must keep your sensitive information safe, not just your company’s but also your customer’s information.
Losing your sensitive data is terrible, of course, but if you lose your customers’ private information, that’s just as bad, if not worse. Your business will see its reputation damaged, and customers will have difficulty trusting you.
Another vital piece of data integrity is ensuring it maintains its original cohesion and original state; that’s how your data stays valuable. It doesn’t just get pulled and remain stagnant in one spot; as you transfer, store, and access it, you run the risk that it becomes altered. It’s essential that doesn’t happen.
Data integrity is critical at every stage of data. It allows for easier access, tracing, and searching. Data transparency makes every step along the way more manageable and more accurate. In addition, it ensures that your data is stable. Sadly, only 35% of global senior executives highly trusted their company’s use of data in a survey done by KPMG International.
How to Get and Maintain Data Integrity
You can take matters into your own hands and get started today to ensure your data integrity. You’ll be on your way by implementing a few specific procedures and routines.
Begin with High-Quality Data
Streamline your collection method before you even begin to gather your data.
Only collect the data you require, right from the beginning. Don’t waste your time and energy sorting through the information you’ll never even use.
Before gathering your data, ensure it’s reliable, accurate, and fully there. Why bother pulling what you don’t need only to spend time later weeding it out?
Evaluate your data before collecting it, and revisit your methods and parameters often.
Remove Redundant Data
Clean out your duplicate data frequently. It’s natural that you will get redundant information, but don’t let it sit there, taking up space and causing confusion.
Simply make it a part of your routine to process and clean out your repetitive numbers.
Perform Frequent Updates
As your data ages, it becomes less accurate. Therefore, old info is outdated info.
Fresh data brings more reliability with it since it reflects any recent changes. Therefore, refresh your data regularly for the most accurate, up-to-date information.
Assess for Mistakes
To err is human, of course, but your data isn’t forgiving.
Regularly check over your collection to spot any human errors that may have occurred. And don’t just rely on one person to get it done; have multiple eyes look it over so that nothing gets missed. Implement a system of checks and balances with a schedule for reassessing your data.
Trust your data, but verify.
Educate Your Employees on Data Integrity
Every employee who comes into contact with your company’s data needs to understand and appreciate the importance of data integrity. They need to understand the why and the how, too, not just to be told: “just do it.”
Educate your employees who work with data on what your plan is for implementing and maintaining data integrity. Then, when everybody is on the same page, looking out for your data, it will be better protected.
Data is at the heart of all your business decisions, so your business needs to have the best information possible. Without data integrity, you’re entering a guessing game; it may or may not end well. Data can be the road to fantastic business opportunities, but it can also be the road to failure if it’s unreliable. Culling your company’s data is only the beginning of the data process; the real work comes with ensuring integrity.