Learn Microsoft Fabric Basic to Advance with Practical

سرفصل های دوره

Microsoft Fabric End to End Analytics, Data engineering with Fabric, Certification, Real time analytics Fabric tutorial

1 - Introduction

1 - Setup Account with Microsoft Fabric

2 - Walkthrough with Features of Microsoft Fabric

3 - Microsoft Fabric Architecture

2 - Lakehouse

4 - Introduction to Lakehouse OneLake

5 - Setup your first Lakehouse Ingest Data

5 - sales.csv

6 - Delta format tables

7 - SQL Endpoints

8 - Data Visualization in Spark Notebook

9 - Visual Query Editor

10 - Create Report

3 - Data Processing with Apache Spark

11 - Introduction to Large Scale Data Analytics

12 - Apache Spark

13 - Spark Settings in Microsoft Fabric

14 - Setup your first Notebook

15 - DataFrame from Lakehouse

16 - Data Transformation Saving the Transformed Data and Partitioning using PySpark

17 - Parquet File Partitioning in Spark RDD

4 - Delta Tables in Microsoft Fabric

18 - Load Data into Spark Dataframe

19 - Managed and External Tables

20 - Data Insertion in Delta Table

21 - Table Updation and Table Versioning

22 - Create Delta Table from Streaming Data

5 - Data Pipelines in Microsoft Fabric

23 - SparkSQL API to process data

24 - ETL Extract Transfer and Load

25 - Pipeline Copy Data Activity Delete Data Activity and Notebook Activity

26 - Variable in Pipeline

27 - Run and Monitor Pipeline

6 - Ingest Data with Dataflow gen2

28 - Copy Data Transform Data using Dataflow

7 - Data Warehousing in Microsoft Fabric

29 - Introduction to Data Warehouse

30 - Dimensional Modelling in Data Warehouse

31 - DW-Queries.txt

31 - Setup your Data Warehouse in MS Fabric

32 - Query your Data Warehouse

33 - Visual Query Editor in Data Warehouse

34 - Performance Monitoring in Warehouse

8 - Real Time Data Analytics

35 - Introduction to Real time Data Analytics

36 - Setup your KQL Database

36 - sales.csv

37 - Data Processing and Analysis using KQL QuerySet

38 - Data Visualization

9 - Data Science with Microsoft Fabric

39 - Introduction to Data Science Predictive Analytics and Machine Learning

40 - Notebook Experiment and Run

41 - Setup and load data into Notebook

42 - Create Experiment and Build your Model

43 - Compare an Save your Models

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تولید کننده: Udemy-Training