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2 Real World Azure Data Engineer Project End to End

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2 Real World Azure Data Engineer Project End to End, available at $64.99, has an average rating of 4.27, with 33 lectures, based on 1014 reviews, and has 8865 subscribers.

You will learn about You will learn how to Architect, Design and build a real-world enterprise level data platform solution including multiple services. You will learn design solution using ADF, Azure Function, Databricks, pyspark, Azure Data lake storage Gen 2 (ADLS), Azure SQL Server You will learn how to build a real-world data pipeline in Azure Data Factory (ADF). This course has been taught using 2 real world use case scenarios. You will learn how to transform data using Databricks Notebook Activity in Azure Data Factory (ADF) and load into Azure Data Lake Storage Gen2 You will learn how to build production ready pipelines and good practices and naming standards You will learn how to integrate Databricks with ADF and send the response back from Databricks to ADF You will learn how to develop the triggered based Azure Function to validate files. You will learn how to create Azure Key vault and use it to store secret credentials and SAS token You will learn how to connect the Azure SQL Database and Databricks cluster using the Key Vault You will learn how to mount he Azure Storage Account in the Databricks to access the files and preform transformation on it. You will learn how to transform the data in the Azure Databricks using the pyspark. This course is ideal for individuals who are Aspiring Data engineer who are searching for project to add in resume or Someone who is looking for Real World uses cases to implement as Data engineering Solution or University students looking for a career in Data Engineering or IT developers working on other disciplines trying to move to Data Engineering or Data Engineers/ Data Warehouse Developers currently working on on-premises technologies, or other cloud platforms such as AWS or GCP who want to learn Azure Technologies or Data Architects looking to gain an understanding about Azure Data Engineering stack or Data Scientists who want extend their knowledge into data engineering It is particularly useful for Aspiring Data engineer who are searching for project to add in resume or Someone who is looking for Real World uses cases to implement as Data engineering Solution or University students looking for a career in Data Engineering or IT developers working on other disciplines trying to move to Data Engineering or Data Engineers/ Data Warehouse Developers currently working on on-premises technologies, or other cloud platforms such as AWS or GCP who want to learn Azure Technologies or Data Architects looking to gain an understanding about Azure Data Engineering stack or Data Scientists who want extend their knowledge into data engineering.

Enroll now: 2 Real World Azure Data Engineer Project End to End

Summary

Title: 2 Real World Azure Data Engineer Project End to End

Price: $64.99

Average Rating: 4.27

Number of Lectures: 33

Number of Published Lectures: 33

Number of Curriculum Items: 33

Number of Published Curriculum Objects: 33

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

  • You will learn how to Architect, Design and build a real-world enterprise level data platform solution including multiple services.
  • You will learn design solution using ADF, Azure Function, Databricks, pyspark, Azure Data lake storage Gen 2 (ADLS), Azure SQL Server
  • You will learn how to build a real-world data pipeline in Azure Data Factory (ADF). This course has been taught using 2 real world use case scenarios.
  • You will learn how to transform data using Databricks Notebook Activity in Azure Data Factory (ADF) and load into Azure Data Lake Storage Gen2
  • You will learn how to build production ready pipelines and good practices and naming standards
  • You will learn how to integrate Databricks with ADF and send the response back from Databricks to ADF
  • You will learn how to develop the triggered based Azure Function to validate files.
  • You will learn how to create Azure Key vault and use it to store secret credentials and SAS token
  • You will learn how to connect the Azure SQL Database and Databricks cluster using the Key Vault
  • You will learn how to mount he Azure Storage Account in the Databricks to access the files and preform transformation on it.
  • You will learn how to transform the data in the Azure Databricks using the pyspark.

Who Should Attend

  • Aspiring Data engineer who are searching for project to add in resume
  • Someone who is looking for Real World uses cases to implement as Data engineering Solution
  • University students looking for a career in Data Engineering
  • IT developers working on other disciplines trying to move to Data Engineering
  • Data Engineers/ Data Warehouse Developers currently working on on-premises technologies, or other cloud platforms such as AWS or GCP who want to learn Azure Technologies
  • Data Architects looking to gain an understanding about Azure Data Engineering stack
  • Data Scientists who want extend their knowledge into data engineering

Target Audiences

  • Aspiring Data engineer who are searching for project to add in resume
  • Someone who is looking for Real World uses cases to implement as Data engineering Solution
  • University students looking for a career in Data Engineering
  • IT developers working on other disciplines trying to move to Data Engineering
  • Data Engineers/ Data Warehouse Developers currently working on on-premises technologies, or other cloud platforms such as AWS or GCP who want to learn Azure Technologies
  • Data Architects looking to gain an understanding about Azure Data Engineering stack
  • Data Scientists who want extend their knowledge into data engineering

This course will help you in preparing and mastering your Azure Data engineering Concepts.

It is not like any random project like covid, or twitter analysis. These project is real world projects on which I personally worked and developed it for big clients.

Highlights of the Course:

  • Designed to keep only précised information no beating around the bush. (To save your time).

  • Real time implementation, no dummy use case.

  • Can be added as part of your resume.

  • It will help you to showcase your experience in interviews and discussion.

  • Involve complex architecture solution which is aligned with industry best practices.

  • Single projects involve various component integration like ADF, ADLS, Databricks, Azure SQL DB, Key Vault.

  • Solves the problem of real time experience for new Data engineers.

This course has been developed in mind to keep all the best practices followed in the Industry as an data engineering project and solution.

Technologies involved:

  1. Azure Data Lake Storage Gen 2

  2. Azure Data Factory

  3. Data Factory Pipeline

  4. Azure Functions

  5. Azure Key Vault

  6. Azure SQL DB

  7. SSMS

  8. AWS S3 Bucket

  9. Connect ADF to Databricks

  10. Connect Databricks to SQL Server

  11. Connect Databricks to ADLS

  12. Connect S3 to Azure Cloud

  13. Triggers

  14. SAS token

  15. Create Secrets scope in Databricks

  16. Store secretes in Key Vault and access them

What you will learn after this course:

  • How to think, design and develop the solution in the data engineering world.

  • How to create the architecture diagram for data engineering  projects.

  • How to Create Azure Data Factory Account

  • How to Create Azure Data Lake Storage Gen 2 account.

  • How to Create Azure Databricks Workspace.

  • How to create S3 storage account.

  • How to create Azure Function.

  • How to implement logic in the Databricks notebook using pyspark.

  • How to connect ADF to Databricks.

  • How to chain the multiple pieces together in project.

  • How to create Azure SQL Server.

  • How to load the data from file to Azure SQL server.

  • How to connect Databricks notebook with Azure SQL Server.

  • How to Store secrets in the Azure Key Vault.

Course Curriculum

Chapter 1: Project 1: Smart Vehicles

Lecture 1: Understand the Vehicle System Use Case

Lecture 2: Create Architect Diagram for Vehicles Data engineering Solution

Lecture 3: Practical Lab: Create S3 bucket in the AWS Account and upload data.

Lecture 4: Practical Lab: Create ADLS Storage account(Landing Folder)

Lecture 5: Practical Lab: Create Azure Data Factory Account For Data pipelines

Lecture 6: Practical Lab: Create Azure Key Vault and Add the secrets

Lecture 7: Practical Lab: Create Pipeline End to end pipeline with triggers enabled

Lecture 8: Practical Lab: Create Azure Function with blob trigger logic

Lecture 9: Azure Function: Update the JSON Format

Lecture 10: Create Azure SQL Server and Database

Lecture 11: Practical Lab: Add another pipelines for moving data from Staging to SQL DB

Lecture 12: End to End Testing

Chapter 2: Project 2: AP Morgan Data Platform

Lecture 1: Project 2: AP Morgan Data Platform Introduction

Lecture 2: Project 2: Architecture Diagram

Lecture 3: Practical Lab: Create Azure Data Lake Storage account and Drop input files

Lecture 4: Practical Lab: Create Azure Databricks Account Workspace

Lecture 5: Practical Lab: Azure SQL Server

Lecture 6: Practical Lab: Connect SQL DB with SSMS and Create MetaData / Schema table

Lecture 7: Practical Lab: Azure Key Vault to keep SQL server password and SAS token Lab

Lecture 8: Practical Lab: Create a secrets scope in Databricks

Lecture 9: Practical Lab: Create Cluster in Azure Databricks

Lecture 10: Practical Lab: Add notebook in Databricks and Implement the Business Logic

Lecture 11: Practical Lab: Azure Data Factory For AP Morgan

Lecture 12: Practical Lab: Create Azure Databricks Linked Service in ADF

Lecture 13: Practical Lab: Create ADF Pipeline to call Notebook and Test End to End Flow

Chapter 3: Azure Data Factory Quick Walk through

Lecture 1: Azure Data Factory Introduction

Lecture 2: Lab: Create Your First ADF Pipeline

Lecture 3: Lab: Parameterized Dataset in ADF

Chapter 4: Intergration Runtime and Triggers Azure Data Factory

Lecture 1: Integration Runtime

Lecture 2: Lab: Schedule Trigger in ADF

Lecture 3: Lab: Tumbling Window Trigger in ADF

Lecture 4: Lab: Storage Event type Trigger in ADF

Chapter 5: Data Flow in ADF

Lecture 1: Learn Data Flow in Azure Data Factory

Instructors

  • Deepak Goyal
    Deepak Goyal
    Microsoft Certified Trainer | Architect| Top Voice LinkedIn

Rating Distribution

  • 1 stars: 29 votes
  • 2 stars: 21 votes
  • 3 stars: 111 votes
  • 4 stars: 360 votes
  • 5 stars: 493 votes

Frequently Asked Questions


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You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


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