Organizations across the globe are collecting more data than ever before, and many of them are struggling to keep track of what data they store, who collected it, why it was collected, and how it is being accessed and used. It’s important to remember that data is very valuable.
Companies can use the data they collect to derive meaningful insights into consumer and industry trends. Cyber-criminals want to get their hands on this data in order to sell it on the dark web or use it for other nefarious purposes.
Without a well-thought-out data governance strategy, companies will put their customer’s privacy at risk, fall out of alignment with the relevant data privacy laws, and fail to use the data to maximize their productivity. Below are some of the main challenges that organizations will encounter when developing and maintaining a data governance program.
1. Limited Resources
In general, organizations are not overly keen on the idea of allocating large amounts of their budget to data security, as it doesn’t appear to yield any direct rewards. As a result, many security teams are required to operate on a tight budget and are usually too busy with other tasks to focus on improving/updating their data governance program.
The problem is that a failure to do so could end up costing them more resources in the long run. Not only is it important to ensure that you have a sufficient level of funding and staff to maintain your data governance program, but it’s also a good idea to focus on automating as many tasks as possible, which includes carefully selecting the right technologies and streamlining business processes.
2. Data Silos
Data security techniques, such as micro-segmentation, can help to make networks less vulnerable to attack. However, such techniques require planning and consideration. When data becomes unintentionally siloed, it will become even harder to protect. For example, when companies collect too much data too quickly (which is often the case), it tends to get scattered around in unknown, unmonitored, or unsuitable locations.
Data can become siloed when companies adopt new technologies, data sources, processes, or infrastructure. In some cases, all it takes is a bit of friction between teams/departments for data silos to form. It is important that we pay close attention to the processes that determine how and where our data is stored, otherwise, we will struggle to keep it secure, or use it in a meaningful way.
3. A Lack of Leadership
Many companies lack leadership when it comes to data governance – a problem that is exasperated by the serious lack of cyber-security professionals. In the absence of a dedicated data governance officer, it is necessary to appoint a member of staff who will give directions to the security team, develop policies, discuss ideas, address concerns, deliver presentations, and so on.
4. Managing ROT Data
Organizations collect and store large amounts of data that isn’t really useful to them or their customers. This type of data is typically referred to as ROT (Redundant, Obsolete or Trivial). Hoarding large amounts of ROT data is generally a bad idea as it creates clutter and hinders visibility.
To ensure that organizations are only storing the data they need, they will need a solution that will automatically discover and classify their data, based on whether it is public, private, or restricted. Some data classification solutions will also come with pre-sets that allow you to classify data in accordance with the relevant data privacy laws. You may also want to consider using a data deduplication solution that will scan your repositories for duplicate files, and replace them with a reference to the original file.
5. A Lack of Control
Naturally, if you don’t have control over your assets, you will likely fall out of compliance with the relevant data privacy laws. In cases where organizations are overwhelmed by the amount of data they collect, they will often just store the data anywhere they can, without concerning themselves about who is responsible for it. If nobody is responsible for it, then you won’t have control over it. Again, you will need a data classification solution that can automatically classify data at the point of creation/modification, which the relevant personnel can review for inconsistencies.
Perhaps the most important area of data governance is visibility, as without visibility you won’t have control. You need to know what data you store and where it is located. You need to know which documents contain sensitive information, and you need visibility into how the data is being accessed and used.