Master Microsoft Fabric: Data Engineer to Real-time Insight

Master Microsoft Fabric: Data Engineer to Real-time Insight, available at $44.99, has an average rating of 4.33, with 59 lectures, based on 3 reviews, and has 12 subscribers.

You will learn about Lakehouse Datafactory Dataflowgen-2 Notebook using pyspark Data Warehouses Realtime Intelligence This course is ideal for individuals who are This course is designed for professionals in data analysis, data science, data engineering, Power BI development and other professional. or Curious beginners eager to learn this Microsoft Fabric key skills. It is particularly useful for This course is designed for professionals in data analysis, data science, data engineering, Power BI development and other professional. or Curious beginners eager to learn this Microsoft Fabric key skills.

Enroll now: Master Microsoft Fabric: Data Engineer to Real-time Insight

Summary

Title: Master Microsoft Fabric: Data Engineer to Real-time Insight

Price: $44.99

Average Rating: 4.33

Number of Lectures: 59

Number of Published Lectures: 59

Number of Curriculum Items: 59

Number of Published Curriculum Objects: 59

Original Price: ₹799

Quality Status: approved

Status: Live

What You Will Learn

Lakehouse
Datafactory
Dataflowgen-2
Notebook using pyspark
Data Warehouses
Realtime Intelligence

Who Should Attend

This course is designed for professionals in data analysis, data science, data engineering, Power BI development and other professional.
Curious beginners eager to learn this Microsoft Fabric key skills.

Target Audiences

This course is designed for professionals in data analysis, data science, data engineering, Power BI development and other professional.
Curious beginners eager to learn this Microsoft Fabric key skills.

Unleash the power of your data for deeper insights!

Microsoft Fabric is a comprehensive suite of cloud-based data management and analytics services designed to simplify your data journey. This course equips you with the knowledge and skills to leverage Fabric’s components to:

Ingest data from various sources like lakhehouse, cloud storage, and web APIs.
Transform and prepare data for analysis using intuitive visual tools and powerful data manipulation capabilities.
Store and manage data in a secure and scalable data lakehouse environment.
Analyze data with familiar SQL queries and interactive notebooks.
Build data pipelines to automate data processing tasks.
Gain insights from your data through powerful visualizations and reporting tools.

Key Components of Microsoft Fabric:

Azure Data Factory (ADF): Your central hub for building data pipelines that automate data movement and transformation.
Fabric Data Warehouse: A fast and scalable data warehouse powered by SQL, enabling you to analyze historical data for trends and insights.
Lakehouse: Combines the flexibility of a data lake with the structure of a data warehouse, allowing you to store and analyze all your data in a single platform.
Dataflow Gen2: A visual data workflow builder that simplifies data ingestion and transformation with drag-and-drop functionality.
SQL Analytics Endpoint: Provides a familiar SQL interface for querying data stored within your data lake.
Workspaces: Centralized locations to organize and manage your data objects, reports, and applications.
Integration with Power BI: Leverage the popular Power BI tool for interactive data visualization and reporting based on your Fabric data.
Realtime Intelligence: Explore major use case of Realtime Intelligence with visual interface

By the end of this course, you’ll be able to:

Understand the core concepts of Microsoft Fabric and its components.
Build data pipelines using Azure Data Factory.
Explore and analyze data using the Fabric Data Warehouse and SQL queries.
Leverage notebooks for interactive data exploration and analysis.
Manage and collaborate on data projects within Fabric workspaces.
Gain valuable insights from your data to make informed decisions.

Ready to unlock the potential of your data? Enroll now and start your data analysis journey with Microsoft Fabric!

Course Curriculum

Chapter 1: Introductions

Lecture 1: What is Microsoft Fabric

Lecture 2: What is workspace and how to create it

Chapter 2: Data Factory in Microsoft Fabric

Lecture 1: What is Pipeline in Data factory

Lecture 2: What is Data factory and its use case

Lecture 3: Data factory Walkthrough

Lecture 4: What is IF activity in Datafactory

Lecture 5: What is Getmetadata activity in Datafactory

Lecture 6: Get metadata with IF scenarios

Lecture 7: What is foreach activity

Lecture 8: What is lookup activity in data factory

Lecture 9: lookup activity with foreach activity scenario wise

Lecture 10: What is switch activity & Parameter

Lecture 11: Switch activity with Paramter use case scenario wise

Chapter 3: Datawarehouse in Microsoft Fabric

Lecture 1: What is Data warehouse in Microsoft fabric

Lecture 2: Datawarehouse Walkthrough

Lecture 3: Get Data Approach using Pipeline in Datawarehouse

Lecture 4: Get Data Approach using Dataflow gen2 in Datawarehouse

Lecture 5: Creation of Dimension table and Fact table in Datawarehouse by scenario-1

Lecture 6: Creation of stored procedure scenario-2

Lecture 7: What is T-sql in microsoft Fabric

Lecture 8: TSql commands use case of -Create, Copy, CTAS

Lecture 9: New sql query use case

Lecture 10: Notebook use case in Lake house

Lecture 11: What is Semantic Model in Lakeh ouse

Chapter 4: Lakehouse in Microsoft Fabric

Lecture 1: What is lake-house in Microsoft Fabric

Lecture 2: What is workspace

Lecture 3: Workspace and lake house creation in Microsoft fabric

Lecture 4: Get data approach for file upload in lake house

Lecture 5: Get_data using Pipeline in lake house.

Lecture 6: Get data using Dataflow gen2 in lake house

Lecture 7: Get data using Event streaming in lake house

Lecture 8: What is Semantic Model in Lakehouse

Lecture 9: Semantic model use case in Lakehouse

Chapter 5: Dataflow Gen2 in Microsoft Fabric

Lecture 1: What is Dataflow Gen2 in MF

Lecture 2: Dataflow Gen2 walkthrough and creation of sample data set

Lecture 3: Dataflow gen2 Transformation(Filters, split columns, rename etc

Lecture 4: Data flow gen2 Transformation (joins, group by etc)

Lecture 5: What is Spark

Chapter 6: Pyspark for Data engineer in Microsoft fabric

Lecture 1: What is Notebook in Microsoft fabric

Lecture 2: Notebook walkthrough and sample creation

Lecture 3: Filter creation using Pyspark

Lecture 4: Joins using Pyspark

Lecture 5: Aggregation using Pyspark

Lecture 6: Union using pyspark

Lecture 7: Rank using pyspark

Lecture 8: Pivot using pyspark

Lecture 9: Unpivot using pyspark

Lecture 10: Write method using pyspark

Lecture 11: What is Delta table and how to create it

Chapter 7: Realtime Time Intelligence in Microsoft fabric

Lecture 1: What is Realtime Intelligence

Lecture 2: What is KQL DB

Lecture 3: What is event stream in Realtime intelligence

Lecture 4: What is KQL query

Lecture 5: What is KQL query set its usecase

Lecture 6: Use-case of KQL DB and KQL query in realtime intelligence

Lecture 7: Event streaming approach loading data to lake house

Lecture 8: Data-loading to KQL DB using Event stream

Lecture 9: Event house Walkthrough in Realtime Intelligence

Lecture 10: END To END project by using Event streaming for OTT data api

Instructors

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