Data is one of the most common yet important elements of our life, at least in 2020. Data storing has become so important that you are necessarily buying such devices that have a huge memory to store this data.
It’s pretty obvious that organizations depend on this data as well. How else would they be able to reach out to you and dwell, right? At least for every organization, there’s an employee record. That contributes to data.
Data as such could be stored in enormous volumes which makes it really hard to identify. Finding specific data that’s important to you is like finding a needle in a stack of hay. Not unless you have a proper data classification system around.
Data Discovery and Classification
Data Discovery and Classification aren’t really that distinct. Both have a lot of similarities and could be beneficial together for an enterprise.
Data Discovery basically allows you to scan the environment for determining where data of all types and forms are present.
Data Discovery has a lot in particular with content auditing as it can thoroughly audit all kinds of sensitive or regulated information including personal and proprietary data and present them to you.?
On the other hand, data classification is a more complicated process than data discovery. Data Discovery involves identifying all the types of data within the discovered data sources.
This is done with the help of a predefined set of rules, patterns, or keywords that are specified to sorting the said data accordingly.
It is more like labeling a particular type of discovered data under a certain category.
Data Discovery and Classification: Importance
If you are an organization or enterprise that withholds sensitive data, you might already be aware as to how vulnerable this data is if you don’t protect it efficiently.
Enterprise data moves from one location to another and is stored at countless locations, right from a user’s computer to his online cloud services and applications. Employees, customers, or business partners could access this data from any device, be it secure or not which ultimately poses a risk to such data.
The verdict here is that the discovery and classification of data are important fundamentals to rightly treat and protect your data. This also involves all the policies that you need to place around it and guide the same prioritization of your data protection to risk mitigation activities.
These fundamentals every helo you in identifying the data that are governed by regulations to finally allow you to implement the necessary controls to achieve compliance.
Why the linkage between data discovery and classification is beneficial?
At this point, we already know that data discovery and data classification go hand-in-hand. And because of this alignment in their characteristics, it has also proved to be beneficial for enterprises.
It increases the visibility into your data
Data discovery is a common approach towards organizing the data that?s important to the enterprise.?
Discovering a particular feature or segment of a file and discovering something within such files is more of a traditional approach.
Data Discovery, however, identifies what kind of data is eligible for classification. And that’s not all. It even understands where data is likely vulnerable and where it could be breached, thus sealing the gaps. Together, these contribute to a more secure network within an enterprise.
In accordance with compliances
When it comes to data protection, classification is important in a compliance environment as you can find data like PHI or PCI which are subject to regulations.
Through data discovery methods, you can ensure data doesn’t exist in the non-compliance locations. And when it moves, you can make sure it?s done in a controlled and appropriate way.
In case a certain amount of data is flowing through specific mediums like emails, data transfers, USB, etc, the presence of discovery would limit the scope of the data present to just classified data.
With such a limiting scope, your main focus could be the resources on the most important data.
Discovery and classification do de-emphasize the unclassified data. However, because of the fact that you are always monitoring different kinds of data, you could also detect any misuse involved with the unclassified data.