Overview of security concepts and settings for data platforms built on Azure to harden interfaces and endpoints
scieneers GmbH offers consulting and implementation for your analytical data projects. From data we gain insights and create value. For our customers, society and ourselves. This is the englisch version of the description - see also the German version attached below.
A data application built on Azure PaaS components like Data Lake, Data Factory or SQL Azure can be set up in a short time. Thanks to various documentation available, even beginners can build great functionality with it. A secure baseline and rule set is mandatory for internet exposed services and live data, but it‘s often missing or incomplete in real world projects or planned to be done later. Since much data is still stored on premises the connectivity to load this data secured to Azure is one of the first and most important questions to be answered for any project. Other themes are the proper handling of secrets in a public cloud, how to secure network connectivity between the components and implementing data viewing thus everyone sees only his data.
In the briefing we cover the following topics:
Not all what’s technically possible is always the best way to go. We‘ll show examples where avoiding technical options make data apps even stronger or more robust without them.
After the briefing the customer will have a deeper understanding of common security topics and best practices. Most of them will afterwards take a closer look at their own Azure services configurations.
Briefing could be held in English or German language.