Data Security as a Basis for Data Democratization

Collecting data is nothing new for businesses. But it is only gradual that the realization is gaining that no progress can be made with hoarding masses of data. It is important to make use of the collected treasures. Especially in the past twelve months, as in many other areas of digital transformation, companies have set in motion. And time and again, the term data democratization” is used to help advance the topic of big data analytics in organizations.

What exactly is behind this and what can companies derive from it for themselves? Gartner is saying that data democratization was already one of the ten most important strategic technology trends of the coming years in 2020. In practice, however, most companies have not yet understood how crucial data democratization is to their business success – and if they do, implementation is the big problem. So how can companies benefit from data democratization and what do they need to consider to put the concept into practice?

Hierarchies make no sense

Data democratization aims to enable every employee – even beyond the designated data specialists – to collect, analyze and use data independently. This is not just about the topic of tools and skills, but about the corporate culture itself. If the evaluation of data is no longer the responsibility of individuals but is rolled out in the area, this ensures greater equality and freedom for employees. Democratic fundamental values will therefore be strengthened. From this understanding, the first challenge for data democratization is immediately apparent. It is about greater transparency, and that requires a positive attitude in management.

Especially in traditional, hierarchical companies, this can be a challenge for the management to provide every employee with more or less deep insights into the company’s data assets. Here it is important to enter into dialogue with each other at the different management levels, as well as to reduce fears and build trust.

At the same time, employees must be involved in the process. This means, for example, offering training to impart the necessary know-how. To achieve true data democracy, it helps to create the position of Chief Data Officer (CDO) who is responsible for the data in the company. He or she can integrate the knowledge of data into an organization’s daily life, advance data strategy, and ensure transparency.

Good user experience creates acceptance

Of course, a commitment to more data democratisation is not enough. For example, organisations need different instruments. First, an analytics platform that can process large amounts of data quickly, even for more complex queries and thousands of data users. This should be embedded in a robust infrastructure, whether on-premises, in a cloud environment, or even in a hybrid form. There are no patent solutions here, each organization has its special features, requirements and IT strategies.

If non-specialist employees are to learn to analyze data, visualization tools help. They should be intuitive to use, have simple interfaces, and provide quick access to relevant information – all with a good user experience. To find out which BI tools are best, it may be useful to try out different solutions in different teams. Investments will probably be unavoidable here.

Data governance – what is allowed?

The right tools are one thing – just as important are guidelines for how the company wants to handle data in general. This is often personal or sensitive information, for example from customers or suppliers. They must treat employees responsibly, while also complying with the legal regulations. A sound data governance strategy is essential if we want to keep track of this.

Data governance means the holistic management of data in an organization. The aim is to ensure data quality, security and protection by legal requirements. Companies cannot do this in a one-off project. Rather, they need to initiate a durable process in which the data is managed throughout its lifecycle in the organization.

For example, there must be binding rules to regularly delete unused data. At the same time, it is always necessary to check whether data is not collected that has no value for analyses. Have certain values in the database ever been used for analysis or query? If this is not the case, they can be deleted, with automation tools helping to detect and automatically delete such data graves.

Data security as a basis for data democratization

Data governance goes hand in hand with data protection and data security. Here, too, companies must take precautions. Since the introduction of the EU General Data Protection Regulation (GDPR), penalties for infringements can be severe; the fines called maybe in the multi-digit million range. Different data laws exist in different countries.

The best way to ensure data security is through clear authorization management with the help of automated security tools. This means that each employee’s data access is finely regulated depending on the area of responsibility.

The topic of data security shows that we are in a field of tension here: on the one hand, it makes sense for the quality of the analyses that in principle every employee can access all data, but from a security point of view this is impossible. Thus, it is not left to make a conscious choice for certain areas. The decision on this should ideally be made by the Chief Data Officer and his team in consultation with the affected departments and follow a general data strategy.

The road to genuine data democratisation is long and should be designed as agile as possible. There will always be a need for adaptation, discussions and changes on the way to optimal data utilization in the company. But when an organization embarks on this journey, it opens up a whole new dimension of action, the added value of which is priceless and creates real competitive advantages.