Digital information is the most critical asset for any business today, but many organizations don’t have a data classification strategy—they just back up everything.
In theory, this should mean every important data asset is safeguarded, but there’s no guarantee, and you may be overprovisioning your data backup in the cloud or on-premise to replicate unimportant, redundant information while overlooking data that truly matters.
If you want to fully protect your data, you need to classify it, and that starts with discovery.
Data classification begins with discovery
If you are to classify data accurately and comprehensively, you need to start with discovery by scanning your entire environment to ascertain where all your structured and unstructured data is stored. This can include a variety of databases, including email, and sensitive information that may be governed with privacy legislation such as Personal Information Protection and Electronic Documents Act (PIPEDA) and the General Data Protection Regulation (GDPR) in mind.
Discovering your data is the easy part. Classifying means being able to identify it correctly—financial or healthcare data, for example—which is essential for proper data protection. You can’t back up data that’s not been discovered, and you can’t prioritize your data backup without proper classification. It’s also essential for developing and applying data governance to meet compliance obligations.
The more data and systems you have, the more complex the data discovery and classification process, but ultimately you want to be able develop a consistent, coherent strategy that becomes a best practice more and more information is generated by your business operations so that it data protection is automatic and reflects its classification.
Improve accuracy with automation and planning
Data classification, like many processes in a modern IT organization, is something that needs to happen, but it’s not something you want to have to do manually. Ultimately, you need to put a plan in place that automates best practices and the classification process so you can have confidence your essential business information is protected accordingly.
Given that human error from time consuming, repetitive manual processes is often what leads to data breaches and losses, it’s worth investing in a tool that automates data discovery and classification. It should support multiple methods, including a catalog-based search as well as regular expression and patterns. Ideally, you want to be able to search data from directly within a table for best accuracy.
Just as there should be a rhyme and reason to your data backup, there should be one for data classification too. Beyond protecting and replicating it for redundancy in case of a disaster, why are you classifying data? Is it to find payment card data that’s subject to Payment Card Industry (PCI) compliance? Personally identifiable information (PII) that’s subject to GDPR? There are many ways to classify data, and some will fall into more than one bucket.
You should also plan our your data classification process, and start where you think the most sensitive data might reside—patient records if you’re a healthcare organization, and generalyl speaking, customer information, which makes your CRM database a great place to start. However, you also want to think ahead as there are some obvious sources where data classification makes sense, but your discovery process may reveal others in development servers or in shadow IT.
Data classification is a continuum
Much like compliance, data discovery and classification are ongoing processes as your information changes and grows in volume in line with your business. You must always be discovering and classifying data, even as it’s shared and moved, so that it can be properly protected as part of a backup strategy. Automation and good policy enable you to make sure data is discovered, classified, secured and properly backed up as to minimize disruption in the event of any emergency or disaster.