Microsoft Fabric is strongest when the work inside it is repeatable. The moment you have ingestion jobs, notebook runs, warehouse refreshes, semantic model updates, or validation steps that need to happen in sequence, orchestration becomes a first-class requirement rather than an afterthought.

Apache Airflow is a good fit when you want clear scheduling, dependency control, retries, and visibility across the whole pipeline. A DAG gives you a readable contract for how a data flow should behave, which makes it easier to debug failures and easier to explain the system to other engineers.

Real-time pose estimation is one of those problems that looks simple from the outside and becomes interesting immediately once you start handling actual video streams. The core goal is to identify body landmarks quickly enough that the output feels live, which means latency and stability matter just as much as model accuracy.

A good implementation balances three concerns: getting frames into the pipeline efficiently, running inference reliably, and presenting the results in a way that is easy to understand. When the visualization is clear, the technical work underneath becomes easier to trust and easier to demo.

An image classification app is a strong starting point for teams that want to add computer vision without building every layer from scratch. Azure AI Services and Custom Vision make it practical to move from a dataset to a working web app in a way that is approachable for both developers and non-specialists.

The useful pattern is to keep the user interface simple and let the AI service do the heavy lifting. Users upload an image, the app sends it to the model, and the result comes back with a clear label and confidence score. That makes the experience understandable and easy to validate.

Can Databricks Genie make a PowerPoint like this based on my data and use my company template exactly? Can it develop and deploy a web app integrating my Genie space?

I have been stress-testing the new Databricks Genie Code, and it is setting a new bar for AI assistants in enterprise data platform technology.