Your business breathes data. Every bit of information, every log, every profile is your company’s lifeblood. All that information makes your organization go round, and, if put to good work, can help launch your company to whole new heights.
It’s also a goldmine for criminals.
The more data we collect, the bigger the target we paint on our backs. It’s a fact of life. There is no going back once you launch your business, you just need to do all that you can to protect it.
How you go about protecting it, however, matters. If you think that shields alone are what’s going to keep hackers out, then you’re mistaken. Firewalls and encryption are great, yes, but only if you know where all of your data is.
If your data is missing or poorly collected, then you aren’t making the most use of it, and you’ve made it easier for criminals to access your system. The good news is that there are data strategies that help you improve your ability to analyze information while keeping it safe.
Data Governance: The Foundation
Every data strategy boils down to master data governance. By managing your master data and creating a single source of truth, you can cut out data leaks and prep your business so that all your cybersecurity efforts finally start paying off.
Master data management is more than just a system; it’s a whole way to structure data so that there’s only one source of truth. With MDM, you create a single profile for every customer, every product, and even your financial information to eliminate inconsistencies.
Master data governance is a key part of MDM, and works as a framework to keep all your data policies straight.
Now, how does structuring and ordering your data around help with cybersecurity?
Think of a warehouse. If your products are strewn everywhere, with no rhyme or reason, and you barely know where things are, then you won’t be able to tell if and when someone sneaks in and steals something or puts a virus that isn’t supposed to be there.
MDM also sets up a few key data protection features, including:
- Data Ownership: Since you can set who is responsible for what data, you can enhance accountability and control.
- Data Classification: You can easily sort what information needs to be classified, encrypted, and secured without any missing files.
- Data Access: Limit breaches and minimize internal threats by locking data access. This means only those who are authorized can see information, and that data should be locked to what’s essential for their role and nothing else.
- Data Clean-up Policies: Policies that outline how data is stored, retained, and, most importantly, deleted can help keep information relevant at all times while minimizing potential back doors that criminals can use to access your system.
Data Clean-Up Policies: Getting Your Information Ready for Security
The data clean-up policies you create in data governance help in a few key ways:
- Removes inaccurate or corrupt information
- Flags incomplete data, so there are no half-empty files
- Identifies outdated information, duplicates, or inconsistencies
Cleaning a house like this then prepares you for data profiling. Within an MDG and with data clean-up, you can then quickly scan to identify patterns in your data, look for any anomalies, and spot risks ASAP.
If there’s a brand new malware program, for example, you’ll be able to spot it in a flash because it’s an anomaly in your MDG framework.
Data Warehouses: Consolidating Your Information
If all your information is spread across servers and computers (in one office, multiple offices, or even in different countries) then you don’t have a good idea of where it is, which means you cannot create an effective cybersecurity shield around it.
That’s why it’s a good idea to consolidate all your information. You can use a data fabric solution to do this, but where you store, it is what’s known as a data warehouse. Warehouses, unlike databases, save historical versions of files right next to the new file, so you can easily dive in and analyze previous trends as needed.
You can do all that while keeping your information in one place so you can then invest in more effective cyber security and data access control methods.
Data Security: Protecting Your Warehouse
Now that you have policies to better structure your data and a data warehouse to keep it all safely in one location, it’s time to secure it. This can be done with several different methods:
- Access Control: Create a consistent framework of employee roles, and then determine what information they need access to. Implement access control so employees have their own unique login and can only access their information, and nothing else.
- Encryption: Encrypting data unless you have the right access key (part of access control) is an easy and effective way to protect against hackers.
- Network Security: You will need network security features like firewalls, intrusion detection, and prevention systems, and to configure your network settings to best protect against cyberattacks.
- Endpoint Protection: Endpoints are every device that connects to your network, so your employees’ phones, laptops, and even smart watches. Endpoint security protects those devices at home and work to minimize viruses from being carried in from home.
- Employee Training: Along with endpoint protection strategies, you also need to invest in regular cyber-savvy training for employees so they know how to spot threats at home and at work.
- Incident Response Plan: Create a go-to response plan if a threat is detected.
On top of these strategies, there are also several tools that you can then implement. It’s a cinch to use these tools so long as all your data is siloed, stored, and organized:
- AI and Machine Learning Threat Detection: AI and ML can be used to run regular sweeps through even large datasets and spot anomalies immediately. Depending on the threat, they can then automatically run through an automated incident response.
- Zero Trust Architecture: Zero trust architecture models verify and then continuously validate every access request, which is useful when managing remote teams.
- Data Loss Prevention (DLP): DLP solutions monitor and protect sensitive data while minimizing the risk of loss.
Your data protection effort will be much easier to implement and use if your data is properly sorted, cataloged, and stored. Start first with data governance, then clean up your datasets using that new framework, store it all, and then set about protecting it for the best results.