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What is data hygiene?

The term “data hygiene” is used to describe the process of keeping data neat and accurate. Data hygiene is a set of simple practices that help you keep your data organised, accurate, and secure.

A recent study found that nearly 90% of companies have experienced data breaches caused by human error. Poor data hygiene is often the culprit. Data breaches can be costly and cause irreparable damage to your reputation. This especially applies to companies that handle sensitive information. In order to avoid these disasters, it’s important to practice good data hygiene. This means keeping your data organised, accurate, and secure.

Fortunately, there are some simple steps you can take to improve your data hygiene. Even though data cleansing is a time-consuming and costly process, it’s still necessary. In this post, we’ll go through some of the processes that can be automated to improve the quality of your data and make sure your data is clean and secure.


Why is data hygiene important?

Data is a valuable asset. You use it to market products, improve customer service, and make life easier for your employees, customers, partners and others. Data hygiene maintains the quality of your data and prevents problems that can occur when data is incorrect or missing.

Bad data is like a bad cold—it spreads quickly and can make life miserable. Good data hygiene, on the other hand, is like a good immune system—it helps you fight off the bad stuff and stay healthy.

There are many benefits to maintaining good data hygiene. First, it helps you keep your data accurate. When your data is clean and well-organised, it’s easier to find the information you need and make sure that it’s correct. Second, good data hygiene makes your data more valuable. When you have high-quality data, you can use it to make better decisions about your business. Third, good data hygiene can help you save time and money. When your data is in good shape, you can avoid costly mistakes and wasted time spent searching for missing or inaccurate information.

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    Best practices for data hygiene

    It’s important to keep your data clean and free of errors. Here are some best practices for data hygiene:

    1. Delete old files regularly. Delete, for example, all files that are older than 5 years if you do not have a really good reason to keep them.
    2. Keep your data organised by creating folders and labeling them clearly.
    3. Try to avoid keeping duplicates of the same file stored in different locations. Every time you save a version of the file to a new location, you increase the risk of a data security breach.
    4. Keep backups of your data. This way, if something goes wrong, you can restore it from a previous version.
    5. Be careful when sharing data. Make sure that you have permission from the owner before sharing it, and only share it with people who need to see it.
    6. Do not send information in emails or email attachments. This leaves data vulnerable in several locations. An attachment sent to 5 people will be saved indefinitely in 6 copies in 6 different inboxes (yours + your 5 recipients). Instead, share data from a central location. Send links to secure files rather than email attachments.
    7. Input the data you collect into a secure software program or database as soon as you receive it.
    8. Do not use your computer’s recycle bin to store files or documents that you need to keep.


    Clean data is important in relation to sensitive data

    Sensitive data is a special category of personal data that requires extra protection. This includes, but is not limited to, things like social security numbers, driver’s license numbers, and credit card numbers. Good data hygiene is even more important when it comes to sensitive data. Keep your sensitive data clean and organised. Make sure that only authorised people have access to it, that it is stored securely, and that it is regularly backed up.


    A smart way to clean your data

    Here at Safe Online we have created DataMapper to simplify data hygiene for SMBs. DataMapper is a web-based tool that uses artificial intelligence and machine learning algorithms to discover and classify your company’s personal data across various platforms and places. DataMapper finds and flags the personal data you store and sorts it into more than 242 file types and up to 98 categories.

    Read more about DataMapper → 

    Sebastian Allerelli

    Governance, risk, and compliance specialist