Data classification can seem like an overwhelming task, especially for organizations without a solid practice in place. As with any security approach, data classification is both crucial and tempting to avoid. Whether the value is recognized or not, there is a chance that it will be pushed further and further down the priority list in favor of more easily processed items.
In this article, we’ll help you build a case for data classification and fill in some important knowledge gaps to ensure your approach is comprehensive. This will require an investment of resources – time, money and people, in particular – but will, in the long run, help organizations avoid costly mistakes.
What is data classification and why is it important?
Data is the lifeblood of a modern organization. Your data is essential to the development of your business, whatever your sector of activity or your offer. As such, ensuring that your data is secure and easily accessible to the right people is paramount.
At a basic level, data classification refers to the organization of your data by categories to facilitate their access, their use, their exploitation and their security in an efficient way. Proper classification makes it easier to locate and retrieve your data when needed. It is particularly relevant for risk managementcompliance and data security.
Data classification is based on categorization best practices using visual labels and metadata tied to predefined criteria. Of course, you can’t classify what you don’t know. To start, you’ll need to focus on data discovery to assess reach. Data lives in many places in today’s modern world, and it’s just as important. Make sure you are looking at the endpoint, in databases, on network shares, and in the cloud.