By: Karolis Toleikis, CEO & Co-Founder at IPRoyal

If you were to ask any business in the tech sector whether they were “data-driven”, most would provide an enthusiastic positive answer. But if you were to ask them what exactly that meant, you’d likely be met with a lot of unclear hand-waving and answers.

Many businesses exist in a state of data-limbo where key stakeholders understand that data is valuable and consider themselves data-driven, but have no inkling of what truly makes a company data-driven.

In addition to the confusion, data is often seen as a good-in-itself, that is, something that’s just good to have with little regard to quality, sources, or even veracity of information.

Data’s place in a business

Data is only as useful as you make use of it. There’s no underlying greatness to data – it’s mostly just numbers on a digital paper. Turning information into something akin to sacred texts does no good for any company.

Yet, data does have a rightful place in every enterprise. It can serve as a tremendous source of objective truth when it otherwise would be hard to access. A great example is when two departments or teams are arguing about the effectiveness of one or another strategy – both will have their own biases and viewpoints, which will influence decisions.

Data, if recorded correctly and cared for, provides a viewpoint outside the pitfalls of human psychology and interests. So, it serves as the perfect foundation for an independent source of truth.

I stress the importance of the word “foundation”. Data is not a substitute for truth, either. Business leaders should be careful to not blindly follow the insights data provides, primarily because information requires interpretation – and interpretation follows the same pitfalls as human decision making.

There are ways to temper the human influence on data interpretation, but it will always remain. As such, data should be seen as a guide towards good decision making, not as the only source of good decision making.

While my understanding may seem as undervaluing the importance of data, being a good guide to business decision making still makes information tremendously valuable. After all, business rests almost entirely on good decision making.

It would make sense, then, that enterprises should be spending a lot of time on protecting their data. And most do – few business leaders are not concerned about data leaks, hacks, or any other of the wide array of issues associated with storing information.

Yet, I’d like to start out on a different type of protection – protection from internal actors. People often won’t manipulate data intentionally, but they will still make mistakes in various ways.

Ensuring data integrity and quality

While protecting your business data from external actors, unauthorized access, and leaks is of utmost importance, ensuring your business information retains veracity is equally as important. If your business decisions are intended to rest on data, you should be pretty confident that it accurately reflects the real world.

Data governance is a good catch-all term for managing internal processes related to storage, authorization, access, usage, and disposal of data. Far too many enterprises completely forego data governance as a practice.

While implementing data governance can have a multitude of overarching and overlapping goals, maintaining data quality, for most businesses, will be the critical factor. You first want to ensure that decisions are being founded on valid data and then move on to other aspects of governance.

All of it starts with a cultural shift – management should clearly indicate that data is to be treated as a key asset, not just something that you fill out by accident. A lot of further developments rest on the ability to adopt the cultural shift.

Often the next step is defining key roles, stakeholders, and responsibilities for everyone involved in the data governance process. Without clear definitions (such as who manages specific aspects of the warehouse, who owns which data points, etc.), a lot of people will default back to the previous state, leading to quality issues over and over again.

Additionally, data acquisition processes should be evaluated, especially if manual work is involved. Technology can remove a lot of human error, so it’s a good idea to minimize manual entry and management as much as possible. As long as the technology is set up correctly, of course.

Finally, a regular data audit process should be established. Data has a tendency to proliferate in sporadic fashion, which can quickly become overwhelming due to the number of sources and storage places. Auditing can help businesses uncover extraneous information, schedule removals, and help discover inefficiencies or inaccuracies.

Good internal management practices aren’t enough for enterprise-level organizations. While data leaks and hacks are an issue for all types of companies, larger organizations often have more sensitive information that can cause tremendous damage if it reaches the wrong hands.
Protecting data from insiders and outsiders
Data protection, like integrity, starts from the inside. As many people already know, most hacks and leaks happen not due to technological failures, but due to social engineering as humans are often the weakest link.

If they are, then we have to set the stage properly to avoid repeating the same problems many organizations are facing. One of the most effective ways to reduce leaks due to social engineering is access restrictions.

Implementing strict procedures on who, when, and how can employees access data greatly minimizes the risk of leaks. While no system is perfect, enterprises can take a page out of government organizations where access to sensitive information is highly restricted. In fact, in some government organizations all roles get an access level assigned to them. Doing something similar may be highly effective.

Continual training of employees, especially those closely related to data protection and governance is another important aspect. Internal politics within organizations can make it more difficult to follow strict procedures with SMBs being significantly more affected.

While business owners often try to find quick, low-cost solutions to training, data protection is an area where investing into acquiring external expertise is wise. After all, if an enterprise is just starting out in their data governance journey, it’s unlikely that they have enough expertise in-house to make effective changes.

Finally, maintaining the tech stack is another important aspect of data protection. While technology shouldn’t be relied upon for the entire process exclusively, keeping software up-to-date, carefully selecting cloud providers, and evaluating any new introduction into the tech stack goes a long way in preventing data breaches.