msingh025 / poc-best-practis

PocBestPractis

This project was generated with Angular CLI version 12.2.9.

Development server

Run ng serve for a dev server. Navigate to http://localhost:4200/. The app will automatically reload if you change any of the source files.

Code scaffolding

Run ng generate component component-name to generate a new component. You can also use ng generate directive|pipe|service|class|guard|interface|enum|module.

Build

Run ng build to build the project. The build artifacts will be stored in the dist/ directory.

Running unit tests

Run ng test to execute the unit tests via Karma.

Running end-to-end tests

Run ng e2e to execute the end-to-end tests via a platform of your choice. To use this command, you need to first add a package that implements end-to-end testing capabilities.

Further help

To get more help on the Angular CLI use ng help or go check out the Angular CLI Overview and Command Reference page.

Lab 01-Configure a Lakehouse, ingesting sample data and building report : https://learn.microsoft.com/en-in/fabric/data-engineering/tutorial-lakehouse-introduction Lab 02-Analyzing data with Apache Spark:https://microsoftlearning.github.io/mslearn-fabric/Instructions/Labs/02-analyze-spark.html Lab 03-Using delta tables in Apache Spark: Use delta tables in Apache Spark Lab 04-Ingesting data with a pipeline: Ingest data with a pipeline Lab 05-Creating and using a Dataflow (Gen2) in Microsoft Fabric: Create and use a Dataflow (Gen2) in Microsoft Fabric Lab 06- Building a data warehouse in Microsoft Fabric: Building a data warehouse in Microsoft Fabric Lab 07-Training and tracking a model in Microsoft Fabric: https://microsoftlearning.github.io/mslearn-fabric/Instructions/Labs/08-data-science-get-started.html