Data classification is used by organisations to adhere to security, privacy and regulatory requirements when collecting, storing, and processing data
No modern organisation can exist without data but… as important as data collection is, being able to effectively classify and then use that data it is just as, if not more, important.
Data classification is vital for Business Intelligence, security, and most of all, regulatory compliance.
Whether you store your data on-prem (but why would you?) or in the cloud, understanding and classifying it will provide the bedrock for your data security and make compliance with all applicable regulations manifestly simpler.
However, if you prefer a more tangible ROI, then practical and efficient data classification also adds a deeper and richer level to all business intelligence, allowing for more concise and trustworthy business critical decisions.
What Actually Is Data Classification?
Data classification is the term used when a business, institution or individual organises their data (both structured and unstructured) into discrete categories that show the differences between them in a useful way.
Some of the standard classifications commonly used include:
- Public data
- Confidential data
- Sensitive data
- Personal data
What’s The Point Of Data Classification?
Breaking it down to its simplest definition, effective data classification allows an organisation to understand the types of data they’re collecting, retaining and storing and where in their systems they’re doing so, based on its value and sensitivity.
Having modern processes and tools to aid in this allows for:
- More effective prioritisation of security protocols
- Better risk management through improved regulatory compliance procedures
- Improved productivity and business critical decision making by having relevant, real-time, accurate data that’s easily discoverable/searchable
- Huge reductions in the cost to maintain an organisations data through the removal of duplicate or old, no longer used/needed records.
Different Ways To Classify Data
Confusingly, there are many different ways to both categorise and then classify your data, although they all have a similar basis.
The first step is to collate all your data into broad ‘categories such as…
- Content Based – A content-based classification system will look to inspect and then ‘interpret’ your data, looking for issues you highlight such as sensitive information.
- Context Based – A context-based classification method will look at where the data was originally created, where it’s currently stored, any creator tags that may be affixed to it and numerous other variables that act as indirect indicators as to the nature of the data.
- User-Based – Finally, a user-based classification methodology will rely on a manual selection by an individual as to what the data is i.e. public, sensitive, restricted etc.
From there you can look to further classify it. This will often be sector or use specific.
The simplest method would be a three-level classification of your date, Public, Internal and Restricted.
- Public Data – An organisations public data will be, as it sounds, be freely shareable with the public.
- Internal Data – Internal data will be data with a low security threshold. It’s likely all staff within an organisation can see this, but it’s still something that might not be appropriate for the public to see.
- Restricted Data – Finally there’s restricted data. This will be propriety, highly sensitive or both. It’s likely the sharing of this type of data could put an organisation at serious legal or financial risk, so additional steps need to be taken to secure its integrity/security.
Once an organisation has mastered a three-level classification system they can then consider taking the next step to a more complicated version, should it be needed.
Many organisations will use a four or even five level classification system with public being the ‘top’ or most open level.
- Public – As already mentioned, this is data that could be shared with anyone
- Proprietary – Any information specific to an organisation that whilst not public, isn’t sensitive, such as internal processes and the like
- Private – From here the data starts to need better security for items like individuals’ names or account information etc.
- Confidential – As it sounds, confidential data is just that; data that through contractual obligations (NDA’s for example) or other processes, can’t be disclosed; such as contract information or employee reviews.
- Sensitive – Finally we get to sensitive information again; data that could hurt the organisation financially or put it at risk in some other way if it became public such as losing control of its intellectual property.
Benefits Of Classifying Data
As we’ve already mentioned, there are a whole host of reasons to classify data within an organisation, most of them focussing around security, regulatory compliance or improved business intelligence.
Data classification will always be the first step to protecting valuable data. If you don’t first classify data that’s sensitive/confidential/proprietary, then it means you need to protect all your data to the same degree… something which will obviously occur additional costs both in time and resource.
It also means there’s no way of knowing who in an organisation should have access to what, which in of itself can raise a lot of security (and regulatory) issues.
The other major benefit to data classification is one of regulatory requirements.
Many local and international regulatory requirements require an organisation to protect specific types of data such as personal or sensitive (think GDPR or GDPRUK requirements) in a specific manner.
Classifying data correctly makes the job of determining what data needs what security a lot easier.
How To Set Up Data Classification As A Process
By now we should’ve (hopefully) convinced you that classifying your data is a good idea… but you may now be wondering how to go about it.
Don’t worry, we’ll show you how and it’s actually quite simple.
The first thing to do is to actually create a data classification policy for your organisation.
That should include a description of the different types of data you might hold, how they should be classified within a framework, what you hope to achieve from it, who the data ‘owners’ are, who regularly (or ever) handles the data, who is responsible for the data and what regulatory legislation needs to be adhered to in storing and processing it.
The classification of the data should be simple enough to remove all ambiguity as to its appropriate level whilst rich enough to provide context as to why it’s been classified thus.
Once that’s done the data needs to be tagged appropriately, with all sensitive or personnel data an organisation holds being sorted into the right category.
Finally, once it’s been established where the data is stored and its level(s) of sensitivity, appropriate security can be implemented that ensures it’s compliant with all relevant regulatory legislation.
After that, it’s just a case of regularly reviewing the data and the processes that control it to unsure it’s still adhering to current best practises and applicable regulatory requirements (as these both have a way of shifting over time).