Data Matters: The ABCs of a Data Classification Policy to Protect Organizational Data

    By Pohan Lin

    Data is gathered and stored, in one way or another, by every organization and business on the planet. Consumers have to trust that proper care will be taken with this valuable and sensitive information, and those who hold this data have a responsibility in the way it’s stored and used. Cyber predictions on security threats, on both the individual and organizational level, often highlight breaches in the defenses that protect data and personal information held by organizations.

    We generate data each time we search online or send an email, and organizations and businesses generate mass data of their own. But managing the collected data requires a system and a strategy, above all it requires organization. This is where data classification comes in. Data classification is a way of categorizing and managing data, in a way that all employees and members of an organization can understand and adhere to.

    Organization takes the stress out of complex operations, just as proposal software can streamline your approach to giving presentations. An effective data classification policy, can simplify and organize the unwieldy task of storing and protecting data within your organization.

    To make this work, a clear strategy for handling and protecting data is needed. Just as companies need policies and guidance in place to maintain email security, so a well planned and thorough data classification policy is a must. But what exactly should this consist of?

    What is a Data Classification Policy?

    A data classification policy ensures the safe handling and protection of data held by an organization. The policy is generally a document where the various levels of data are listed, described and categorized.

    The document also outlines which individuals have responsibility for handling each type of information, naming those who have access. The document helps individuals know their responsibilities and level of access within the staff structure. The creation of the policy is as important to data protection as prioritizing cloud network security, or vetting potential employees.

    In a sense, a data classification policy is a kind of map or floor plan of your organization’s procedures, responsibilities and categories relating to data security. Because of this, although data classification has certain common elements, each individual policy will reflect the company or group who created it.

    If an organization handles a high volume of financial transactions, for example a bank, there may well be specialist categories and procedures relating to the different groups of customers or financial services, such as a legacy financial system. A university or hospital would need a focus on personal information and records, and have numerous levels of classification relating to these.

    Let’s look at what a data classification policy would normally contain in general terms.

    What Should a Data Classification Policy Contain?

    So, we’ve established that each organization will have their own personalized version of a data classification policy, one that reflects the type of organization and its individual structure. But generally an effective policy normally contains at least four main categories, these are normally something like the following: public, sensitive, confidential, and personal.

    It’s possible to have more categories, but add too many main classifications, and there is the risk of confusion and debate about which category is the appropriate choice, and of crossover between categories.

    The main function of having these main categories is to avoid wasting time and resources on safeguarding data that is not particularly sensitive. For example, in a real estate firm, customers’ personal information would be regarded as personal, whereas a list of the best proptech companies would be useful, but hardly private and personal, and therefore it might be classed as public.

    As with any system that classifies large amounts of data, a data classification policy, in addition to the main categories we looked at previously, will have sub-sections. Rather like a library, or a collection of related software such as the Hadoop Ecosystem (What is Hadoop Ecosystem?). The policy will logically group and organize the data, making it easy to navigate for those who have access.

    In addition to having a small number of main categories, it’s also useful to set clear objectives for treating the data your organization holds. Firstly, there needs to be a commitment to confidentiality, in other words, strict guidance should be given about who is authorized to access sensitive data.

    Integrity is another important consideration. When data is held, there must be a strict understanding that it must be stored in its original form. In other words, data should not be modified in any way, or moved, or deleted.

    There is also the question of access and availability. This means that people with permission to access the data have the ability to do so, and that this should be a smooth and unobstructed procedure.

    Another element a good policy should contain is a glossary. This will be specific to each individual organization, depending on what’s in the document, but it’s a good idea to anticipate which terms might be unfamiliar to some users. It’s important to remember that those accessing the policy may come from very different sections of the workforce or membership. It’s best not to assume that terminology will be universally understood.

    The Benefits of a Data Classification Policy

    A proper data classification policy has the potential to measurably benefit a business or organization. The benefits are not limited to the security team, but can in fact impact the whole organization.

    There’s no doubt that handling huge amounts of data can be unwieldy and somewhat daunting, however, there are systems that can help, for example, it’s worth looking into apache hive vs spark for more information.

    One of the main gains of having a clear and well organized data classification policy, is regulatory compliance. Every country and sector has its own regulations when it comes to protecting data, particularly personal data belonging to clients or customers.

    Organizations such as universities, health care providers, but also charities and businesses, all have to comply with strict regulations governing data retention and storage. Having an effective data classification policy in place, is an absolute must in managing data and adhering to regulations.

    Another benefit of organizing data into a clear classification policy is in budgeting for security. If an organization has a clear idea of what data is highly sensitive and what’s less important and how much of each level is being held, it’s much easier to allocate funding and resources to protecting that data.

    Finally, having a data classification policy also has a beneficial effect on the individual employees or members of an organization. The policy, if done well, gives teams a clearer understanding of their duties in terms of the data that the organization holds; enabling them to work more securely and responsibly. Employees or members of an organization can usually get on board with a new system, such as using an email tracker, if it’s helpful and enables them to perform their role more efficiently.

    Identifying each employee’s role with respect to data security makes it far more likely that data breaches will be avoided, and that each person will take responsibility for safely handling data.

    Though, it’s important to ensure the format of the policy is user-friendly and clear, and that the method of inputting data is as smooth and logical as possible. Taking a low-code, flexible approach to any technology involved, such as autoML platforms is important.

    Data Matters

    For organizations and businesses, the world they operate in is increasingly concerned with security but also integrity and ethics.

    This impacts all aspects of a company or organization’s image, it encompasses questions such as where to find brand ambassadors who will represent the business or group in the right way, but it also covers issues of trust and responsibility regarding data.

    This, along with legislation governing data, means that a data classification policy is vital, for any modern organization. Without properly holding and safeguarding data, there is not only the danger of clients and colleagues being put at risk, but also of prosecution, wasted time and resources, and even a loss of reputation.

    Data classification, like risk analysis and health and safety legislation, is a fundamental building block of your organization’s integrity and legal compliance. It’s not simply a way of organizing the data your organization holds, it’s a manifesto and a road map.

    A sound data classification policy is essential for any organization or business. Knowing what kind of data you hold, how much of it there is, and where to find it, is the only way to effectively protect it.

    For some smaller companies perhaps designing and putting together a data classification policy might seem a challenge. If this is the case, it’s a good idea to rely on the many templates now available. Having a blueprint to work to, can take the heavy lifting away from the task and give a structure. The best templates will have flexible features that enable an organization to adopt and tailor to their particular needs.

    But once in place, whether in a medium sized business or a multinational brand, a data classification policy can help organize and clarify data security, and give peace of mind to those responsible for it.

    Pohan Lin – Senior Web Marketing and Localizations Manager #1:

    Pohan Lin is the Senior Web Marketing and Localizations Manager at Databricks, a global Data and AI provider connecting the features of data warehouses and azure data lake analytics to create lakehouse architecture. With over 18 years of experience in web marketing, online SaaS business, and ecommerce growth. Pohan is passionate about innovation and is dedicated to communicating the significant impact data has in marketing. Pohan Lin also published articles for domains such as SME-News.


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