Download and Learn Data Engineering with Microsoft Azure Udacity Nanodegree Course 2022 for free with google drive download link.

Master the job-ready skills you need to be a successful Microsoft Azure data engineer and start learning how to design data models and perform other tasks using Microsoft Azure.

What You’ll Learn in Data Engineering with Microsoft Azure Nanodegree

Data Engineering with Microsoft Azure

Estimated 4 months to complete

Master the skills necessary to become a successful Microsoft Azure data engineer. You will go on a project-based learning journey to learn the skills required to design data models, build data warehouses, build data lakes and lakehouse architecture, create data pipelines, and work with large datasets on the Azure platform.

Data Engineering with Microsoft Azure Intro Video:

Prerequisite knowledge

Experience with SQL, Python, Azure, and Github.

To succeed in this program, you should have:

  • Intermediate SQL programming skills
  • Intermediate Python programming skills
  • Familiarity with the Azure cloud platform
  • Experience with Github

Data Modeling

Learn to create relational and NoSQL data models to fit the diverse needs of data consumers. You’ll understand the differences between different data models and how to choose the appropriate data model for a given situation. You’ll also build fluency in PostgreSQL and Apache Cassandra.

Project – Data Modeling with Postgres

Model user activity data for a music streaming app called Sparkify. Create a relational database and ETL pipeline designed to optimize queries for understanding what songs users are listening to. In PostgreSQL, define fact and dimension tables and insert data into the new tables.

Project – Data Modeling with Apache Cassandra

Model user activity data for a music streaming app called Sparkify. Create a database and ETL pipeline in both Postgres and Apache Cassandra, designed to optimize queries for understanding what songs users are listening to. For PostgreSQL, define fact and dimension tables and insert data into the new tables. For Apache Cassandra, model the data to run specific queries provided by the analytics team at Sparkify.

Cloud Data Warehouses with Azure

Learn how to create cloud-based data warehouses, sharpen your data warehousing skills, deepen your knowledge of data infrastructure, and be introduced to data engineering on the cloud using Azure.

Project – Building an Azure Data Warehouse for Bikeshare Data Analytics

Create a data warehouse solution using Azure Synaps Analytics to better understand Divvy, a bike-sharing program. Start by importing data into Synapse Analytics, then transform the data into a star schema and view reports from Analytics to identify how much time and money is spent per ride.

Data Lakes and Lakehouse with Spark and Azure Databricks

Learn about the big data ecosystem and how to use Spark to work with massive datasets. You will also store big data in a data lake and develop lakehouse architecture on the Azure Databricks platform.

Project – Building an Azure Data Lake for Bikeshare Data Analytics

Build a data lake solution for Divvy bikeshare with Azure Databricks using a lakehouse architecture. Design a star schema based on business outcomes and create a Bronze data store. Create a gold data store in Delta Lake tables and transform the data into the star schema for a Gold data store.

Data Pipelines with Azure

Learn to build, orchestrate, automate, and monitor data pipelines in Azure using Azure Data Factory and pipelines in Azure Synapse Analytics. Run data transformations, optimize data flows, and work with data pipelines in production.

Project – Data Integration Pipelines for NYC Payroll Data Analytics

Analyze how the city’s financial resources are allocated and how much of the city’s budget is being devoted to overtime. Create high-quality data pipelines that are dynamic, can be automated, and can be monitored for efficient operation. Build pipelines using Azure Data Factory for historical and new data to be processed in a NYC data warehouse in Azure Synapse Analytics.

The average salary for a data engineer is $131,769 per year in the United States.

All our programs include:

Real-world projects from industry experts

With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.

Technical mentor support

Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you and keeping you on track.

Career services

You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.

Flexible learning program

Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.

❗❗ Important Must Read ❗❗

Regarding Google Drive, we are only accepting 100 file requests per day because Google has banned our Drive account from publicly sharing larger files. Additionally, some websites are using our files without giving us credit. So we’ve made the course material / file private; you can request it, but it’s first come, first served. We are currently receiving over 6000+ file requests per day.

Now we have all updated Udacity Courses up to June 8, 2022 – new courses, totaling 78 Nanodegree Courses with full Materials (Note: We are the only website on the internet to have all the Updated Udacity Course).

We are no longer offering Dedicated Drives to new users.

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We have Shared Mediafire / download link for Some Courses updated on 2019 in our Telegram Channel and More info about Dedicated Drive and for Support:

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