Some of our community samples have produced great samples that show off the capabilities of Microsoft Fabric. We have collected them here for you to use and learn from.
⚠️ Note: These samples are provided 'as-is' and are not officially supported. Please consider this code as any code you find on Internet and proceed with caution before running it on your environement. If you have any questions, please don't hesitate to ask on the Microsoft Fabric Community.
| Sample | Workloads | Short Description | GitHub |
|---|---|---|---|
| The Foodwaste Hack | lakehouse, Power BI, Data Activator, OpenAI | Combine Power Apps and Fabric to create database of your fridge items and cook-up some great recipes. | GitHub |
| Automating synthetic data creation & reporting using Microsoft Fabric | Lakehouse, Data Science, OpenAI | Create realistic, non-sensitive datasets in place of real, sensitive data. | GitHub |
We want to show you how you can combine Powerapps, Fabric and AI to minimise food waste in your kitchen.
Ever looked into your fridge and thought “darn, should have cooked that chicken sooner?” Worry no more. we have a hack for you.
In our github repo you will find everything you need to create a power app to help track food you have bought, assisted by your own lakehouse with millions of product descriptions, use AI to help with setting expiration dates, and again use AI to recommend some yummy recipe ideas on what to do with your ingredients. The best part? A reflex trigger in Fabric will know when your items are about to go off and automatically trigger your own master chef to suggest some great recipe ideas and email them to you before it is too late!
- Project Repository: https://github.com/AllgeierSchweiz/aihackers
- Video: https://youtu.be/hgCOdZzBuq4
When considering privacy protection in the context of an outsourcing company, synthetic data generation becomes particularly relevant due to the sensitive nature of the data involved. Outsourcing companies often handle data from clients that may contain personally identifiable information (PII), financial records, proprietary business information, and other sensitive data.
By leveraging synthetic data generation techniques, outsourcing companies can effectively manage and mitigate the privacy risks associated with handling sensitive data, thereby building trust with clients, enhancing data security, and ensuring regulatory compliance.