Data hygiene is the process of cleaning up databases of information to ensure they’re accurate, organized, and error-free. In an information security context, data hygiene also involves storing data in secure locations – for example, keeping your passwords in a password manager – and re-verifying staff with access to them.
Today, most companies store vast reams of data relating to customers and employees and rely on it for crucial insights into how their business is faring. This means that maintaining good data hygiene practices has never been more important – crucially, it provides the foundations for informed, assured decision-making.
In this guide, we explain exactly what data hygiene is, the issues you may encounter if you don’t implement good data hygiene practices, and what you can do to keep your company’s records clean and tidy. In this guide, we cover:
What is Data Hygiene?
As we briefly explained above, data hygiene – and more actively, data cleansing – is any process that involves cleaning up datasets and databases to ensure they’re completely accurate, up-to-date, and ultimately usable.
With data breaches now a common fixture of the digital landscape, ensuring you’re storing your data securely is considered a different, but equally fundamental, aspect of data hygiene.
Ensuring good data hygiene practices are being followed should be a cornerstone of any company’s data management processes.
A database of information that has been checked rigorously for errors – and is stored securely – is often referred to as a “clean” set of data. Conversely, data that has not been cleansed or checked for inaccuracies is commonly referred to as “dirty data”.
Causes of Poor Data Hygiene
There are a variety of different factors that can negatively affect the hygiene of a given dataset – and some are more obvious than others.
Outright errors will have the biggest impact on a given dataset’s hygiene, the leading cause of which is human error. However, in an unchecked data set, you may have once correct yet now out-of-date information, which can cause you just as many problems in the context of data hygiene.
Data that isn’t organized very well could also be considered unhygienic. Even if the data itself is correct and up-to-date, if it isn’t compiled in a clear, usable format, you won’t be able to draw out the insights you’d be able to if it was well organized.
Another data hygiene hazard is repeated data – or duplicates – within a dataset. If you have multiple people gathering data and working on it in a centralized location, but you’re not checking it for duplicates, it could significantly affect the conclusions you glean from that information.
A similar thing can be said for ‘irrelevant’ data that may have been added to your dataset but hasn’t been removed despite being no longer needed.
Expert Tip
Data that isn’t organized clearly or stored properly can be just as useless as data that is simply incorrect or out of date. creating this clarity in a business setting should be centered around uniform, well-publicized practices. If everyone in a given company is viewing, inputting, editing, and removing data using the same processes, and contributing to maintaining databases in a specific, pre-determined way, your data is going to be infinitely more useful than it would be if you deploy a scattergun approach.
The Dangers of Storing “Dirty” Data
There are various dangers you’re likely to encounter if you fail to maintain good data hygiene practices within your organization. These include:
- Inefficiency: If you’re relying on inaccurate data for reporting, you’re going to spend a lot of time correcting mistakes, which will appear suddenly and demand immediate attention.
- Poor Decision-Making: Simply put, if you’re using low-quality analytics to make decisions, the decisions will be poorly informed and potentially harmful to your business.
- Data Breaches: If you’re not storing company data securely, you run the risk of exposing it to attackers on the hunt for sensitive information to sell online.
- Compliance Issues: If your data hygiene is poor, then you’re going to face compliance issues which could lead to costly fines.
- Mistrust & Reputational Damage: If your company gets a reputation for poor data hygiene, they’re much less likely to be trusted by clients.
- Lack of Accountability: If your data hygiene is poor, you won’t be able to track performance, praise those who have succeeded, and hold those lagging behind to account.
Poor data hygiene will have different ramifications depending on the industries you’re working in. For example, marketing teams may find themselves blacklisted from certain email inboxes or inaccurate buyer personas.
Sales teams, on the other hand, may ruin customer or client relationships by contacting the same people multiple times for introductory calls if the initial contact or outreach is not logged properly, or the data on these calls is not accessible.
Data Hygiene Best Practice Tips
There are various ways steps you can take to ensure that you’re maintaining good data hygiene practices. In this section, we run through a few concepts and practices that should be part of every company’s data management and storage strategy.
Practice regular data cleansing
Of course, the key component of good data hygiene is regular, thorough data cleansing, during which erroneous records are removed and other related issues, such as duplication, are dealt with.
You can now use AI tools, as well as other tools with automotive capabilities, to aid you in your data-cleansing efforts.
For example, you could use one of these tools to search your database for duplicates and remove them – or you could opt for a data management platform like DemandTools, which will stop them from being added to your database in the first place.
Standardize your data entry
This is a crucial and foundational aspect of a robust data hygiene strategy. You have to set rules – a data “style guide”, if you will – for all of your data inputs.
If you fail to do this, anyone adding information to one of your databases may insert hard-to-detect duplicates, which will cause data reporting and analysis issues.
If you’re collecting customer information, for instance, you’re going to want to standardize salutations (such as Mr. and Mrs.), capitalizations, and how you’re inputting phone numbers.
Other rules should be instated to help deal with entries that have intersecting data points or relate to one another in some way.
How this standardization process is structured will likely depend on the nature and sensitivity of the filters available in the database software you’re using to parse your data for insights.
Standardize your data processes
Standardizing the data you’re inputting is important, but further, standardizing the processes that dictate how you input and make changes is also crucial to ensuring good data hygiene.
For example, there should be a uniform process that governs how you format your data, resolve discrepancies and errors, report changes to databases, merge datasets, and clear up dirty data.
The rules relating to these processes must be clearly communicated to all staff with an interest in a given database or dataset, and critically assessing these rules on a regular basis is essential.
Make calculated decisions about data sharing
Not sharing enough data across departments within your company and creating data siloes is bad for your data hygiene and data visibility. Different departments within the same company could end up using the same data – such as customer information – for different purposes which could easily conflict with one another.
But this has to be balanced with information security best practices like the Principle of Least Privilege (more on this below) to ensure your data isn’t freely accessible to absolutely everyone in your business.
Re-verifying your data
Some people will submit fake email addresses, phone numbers, and other personal information, particularly when entering it into online forms. This means that the data you’re holding will have to be checked to ensure it’s definitely correct before it’s used for anything important – if not, it might waste a salesperson’s time, or be used to build a report that could impact company strategy.
Of course, as well as outright fakes that make for useless data, email addresses can be deleted, and phone numbers changed, so re-verifying your data regularly will ensure there are no discrepancies.
Performing regular data audits
According to a recent Oracle study, over 80% of business leaders feel “paralyzed” by the amount of data their company holds, and don’t trust that it’s accurate.
One thing that can assuage fears like this is regular data audits, within which internal processes are checked over, refined, and improved. Data audits should be continuous, regular, and a core pillar of your data management strategy.
If staff come to expect them frequently, they’re going to hold themselves to a higher standard with regard to their day-to-day data usage than workers at companies where audits are a rarity.
Benefits of Good Data Hygiene
Ensuring good data hygiene is practiced and enforced at your company will have a myriad of benefits, including:
- More efficient working
- Fewer mistakes in data reporting
- More valuable insights from your data
- Minimizing the impact of mistakes/inaccuracies
- A more productive workforce
- Increases in customer and client satisfaction
- Assured decision-making
Remember, the benefits of good data hygiene practices can only be reaped through continuous data cleansing.
According to Acxiom, marketing data is thought to decay at a rate of 2-3% per month – which means around a third of all stored data will need to be cleansed every year.
Data Hygiene and Data Security
Although data hygiene largely refers to keeping the actual data you’re holding mistake-free and “clean” now, data hygiene is sometimes used to refer to data security practices.
Companies holding sensitive data should be deploying the “zero trust” principle to all of their sensitive data sets.
“Zero trust” challenges the assumption that there is a traditional “edge” to a network, inside of which everyone can move freely and access anything they want without identifying themselves. No one, inside or outside of an organization, is to be fully trusted, and constant re-verification is essential.
This is particularly important if you hold PII (personally identifiable information) about customers, as well as employee medical and financial records.
Zero trust architecture – a common feature of many of the best password managers – can be paired with other principles that promote good data hygiene from an information security perspective. This includes the principle of least privilege – the concept that every employee should have access to only the minimal amount of data they need to complete their role and no more.
Investing in cybersecurity tools like password managers can certainly contribute to better data hygiene in a security context, simply because it’ll be more difficult for threat actors to crack passwords.
Final Thoughts: Data Hygiene Today
Following data hygiene best practices is key to ensuring you’re getting the most out of your data, and that people in your company are using it in the right way. Good data hygiene practices can lead to welcome efficiency boosts and accurate reporting.
Companies that aren’t making the most out of the information they hold on customers, clients, and even employees will be left in the dust by those harnessing it to improve their business operations. What’s more, poor data hygiene practices can even lead to reputational damage and monetary fines if compliance regulations aren’t adhered to.
Additionally, as we’ve mentioned good data hygiene also involves storing your data securely. Data breaches are now common, with attackers targeting companies large and small on a near-daily basis, so securing your endpoints with business-focused password managers like NordPass has never been more important. Creating a zero-trust network, and implementing other, related cybersecurity principles across your company network is also essential.