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In-depth articles that go beyond the surface

Practical knowledge on data analytics, cloud, AI and digital strategy — well-founded, honest and written from real projects.

4 articles

October 7 202614 min read

Analytics, data & AI

From individual Power BI projects to a SaaS platform: How smiit Analytics for bexio came about

What started as a series of individual Power BI projects for bexio customers is now an analytics platform of its own. A first-hand account of a business model that didn't work, the architecture decisions that followed and what we learned building it with AI agents.

Editing reports with AI in smiit Analytics: instruction in the chat, the editor updates the report, the AI explains the changes

by Noah NeßlauerRead article

July 22 202614 min read

Strategy, automation & security

Azure Front Door in enterprise architectures: best practices for secure and scalable web applications

Exposing web applications directly to the public internet is easy — but rarely secure enough. How Azure Front Door becomes a controlled, reproducible entry point for modern enterprise web applications as a global edge layer with WAF, Private Link and infrastructure as code.

Azure Front Door as a global edge layer with TLS, WAF, routing and caching, directing requests to edge locations worldwide.

by Sebastian GrabRead article

June 28 202612 min read

Platforms, apps & cloud

Platform economy for IT service providers: turning project business into scalable software products

Building a good software product is only the beginning. How IT service providers turn project-based business into scalable SaaS and platform products — and why success rarely comes down to technology alone, but to strategy, organisation, sales and timing.

The platform as the interplay of the four fields of action: strategy, organisation, technology and sales.

by Noah NeßlauerRead article

May 28 202614 min read

Analytics, data & AI

MLOps on Microsoft Azure: Running machine learning models securely, consistently and at scale

Training a good model is just the beginning. How companies actually get ML models production-ready on Microsoft Azure — from the target architecture through CI/CD, infrastructure as code and a model registry to monitoring and governance.

MLOps as the combination of ML, Dev and Ops

by Sebastian GrabRead article