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Rishi SapraOverview of LDI content for Microsoft Fabric!

Microsoft Fabric is an all-in-one analytics solution for enterprises that covers everything from data movement to data science, Real-Time Analytics, and business intelligence. It offers a comprehensive suite of services, including data lake, data engineering, and data integration, all in one place

Microsoft Fabric Key Concepts

Introduction

  • What is Microsoft Fabric
  • Enabling and using Microsoft Fabric
  • Fabric product experiences and items
  • Key Personas
  • Business Benefits

Key Concepts

  • Compute Engines (SQL/Spark)
  • OneLake
  • Fabric (Power BI) workspaces and domains

Licencing and Admin

  • Fabric licensing model
  • Premium Capacity Management
  • Administer Microsoft Fabric

Working with the Lakehouse and Data Warehouse

Delta Lakehouses

  • Core features of Microsoft Fabric Lakehouses
  • Creating lakehouses
  • Ingesting data in files and tables into a lakehouse
  • Querying lakehouse tables with SQL

Using Apache Spark in Microsoft Fabric

  • Configuring Spark in a Microsoft Fabric workspace
  • Using Spark dataframes
  • Using Spark SQL to query data in tables
  • Visualising data in a Spark notebook

Ingesting Data with Dataflows Gen2 and Data Factory

  • Using Dataflows Gen 2 to ingest and transform data
  • Using Data factory Pipelines
  • Running and monitoring Data Factory pipelines

Data Warehouses

  • Creating and Managing datasets within a data warehouse
  • Querying and transforming data in a Fabric Data Warehouse
  • Securing and monitoring your data warehouse

 

Data Science and Real-time Analytics

Data Science

  • Working with data science processes in Fabric
  • Training models with notebooks in Microsoft Fabric
  • Tracking model raining metrics with MLflow and experiments

Real-Time Analytics in Microsoft Fabric

  • Creating Real-time analytics databases and tables
  • Using KQL to query tables

Building a semantic model and visualising data

The Data Modelling experience in Microsoft Fabric

  • Creating Power BI Datasets from a lakehouse
  • Creating and editing measures, calculated columns and calculated tables
  • Defining row-level security roles and rules
  • Creating new reports based on your data models

Enterprise Model and Report Development With Fabric

  • Understanding Power BI Projects
  • Tabular Model Definition Language (TMDL)
  • Git Integration
  • Deployment pipelines and processes