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In the modern world, data is the most valuable resource that opens new opportunities for development, new ideas and efficient operations. Its value creates high cybercriminals’ interest who steal or corrupt data for their own benefit. Their methods are becoming more sophisticated and inconspicuous, and the consequences become more serious, that incur large financial and reputational losses. The issue of data security is of key importance and is not bypassed by standard security programs.

Data security is a technology set for protecting data from intentional and accidental destruction, alteration and disclosure of data. Most data threats are external, however, don’t neglect the internal data protection system.

Data protection methods include:

• data encryption;
• data classification;
• access definition to data depending on functions and roles;
• data movements and changes monitoring and control;
• creating backups and restoring data.

Many companies outsource some of their work. It’s a common and convenient practice. But  it requires a serious approach to ensuring data security. Companies that care about their customers and data integrity will not give any partner free access to data. Sensitive data (customer information, banking information, confidential information, etc.) needs special protection. The design and implementation of any BI solution must take this into account.

When developing QOps, data security requirements were considered. Data protection and validation is ensured in QOps by:

• separation of source code and data (data is not saved);
• management of access rights depending on the source code storage location.

GitHub, GitLab, Bitbucket hosting systems provide the ability to set up a private or public repository. A private repository implies access to certain users (team members, administrator, etc.). In the situation with public repository everyone has access. Often in hosting systems, public repositories are provided through a subscription. A private repository with corresponding keys assumes a paid basis.

In closed systems, in order to increase data security, separate servers are also allocated for public and confidential data (customer data, phone numbers, email, etc.). Access to such data is severely limited. To protect personal data in Europe, there is a regulation (GDPR), that determines the rules and procedures for such data processing by companies and organizations. Any company that provides a service or sells a product to citizens of the European Union must comply with these requirements.

To comply with GDPR rules and ensure data protection when QOps works with secure Qlik servers, it is possible to connect through QOps Proxy. Thus, the certificate required to connect to the Qlik Server API is located on the same confidential server and does not go beyond it. This prevents the risks of third-party users connecting, taking possession of the certificate and password, as well as gaining access to data in the future. A special authentication method using AzureAD allows to connect the authorized user’s work machine to the QOps Proxy. In turn, the latter, using a certificate, connects to the server and sends only the data and source code to which the user has access.

The complete architecture of the interaction between QOps installed on the user’s local computer and QOps installed in the server environment is as follows. As you can see, this complies with data security requirements and provides flexibility in managing the source codes of Qlik applications using a git-repository, git-runners and a convenient development environment and source code editor VS Code.

More information you will find on QOps website