Identify the data to be secured 

First, it is important to understand that not all information deserves the same degree of protection. Some information is more sensitive than others. Identifying it is critical to ensuring its security. Companies need to catalogue it to get a clearer picture of how much data they have, and how much they need to protect. Then action can be taken. 

Define data access levels 

In a company, some information may be useful to everyone, but other information will only be useful to certain positions or levels of hierarchy. It is important that this data is protected by access levels. This ensures that only the right people can access the files. 

Adopt a multi-model approach 

It is not uncommon to observe data being positioned in silos. The same data can also be found in several silos of varying depth. But data is usually stored on several different systems. When this is the case, the problem of data security becomes more complicated. A multi-model approach to security allows for better data governance and better management of the silos containing the information. 

Opting for anonymization techniques 

Anonymization allows the company to share its data securely, always from a suitable angle and with legitimate targets. Confidential information is replaced, masked or deleted. Anonymization will not be the same in every situation. A system with powerful options for implementing these techniques should be sought. 

Focus on standards 

When it comes to data security, you never start from scratch. It is entirely possible to refer to data security standards. Some require strict access controls, compatible authentication… you just have to make sure that you have software that complies with the standards in force. 

Federating security with comprehensive and flexible rules 

Protecting data from insider threats and breaches while enabling more flexible information sharing is possible. To do this, organizations need to put in place flexible, yet robust and truly comprehensive policies that they can apply to their data. These rules must be based on metadata directly linked to the information stored: author of the modifications made, origin of the data, link with regulations, identity of the employees authorized to consult it, etc. The objective is to establish a complete follow-up of the information and ensure its security. Databases that do not manage to handle these characteristics make data sharing difficult.