Data Engineering with Microsoft Azure v2.2.5

Nanodegree key: nd0277

Version: 2.2.5

Locale: en-us

Learn 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 using Azure Synapse Analytics, Azure Databricks, and Azure Data Factory.

Content

Part 01 : Welcome to the Nanodegree Program!

Welcome to Udacity! We're excited to share more about your nanodegree and start this journey with you!

Module 01: Welcome to the Nanodegree Program!
- Lesson 01: Welcome!
  Welcome to Udacity. Takes 5 minutes to get familiar with Udacity courses and gain some tips to succeed in courses.
- Lesson 02: Getting Help
  You are starting a challenging but rewarding journey! Take 5 minutes to read how to get help with projects and content.

Part 02 : Data Modeling

Learn to create relational and NoSQL data models to fit the diverse needs of data consumers. Use ETL to build databases in PostgreSQL and Apache Cassandra.

Module 01: Data Modeling
- Lesson 01: Introduction to Data Modeling
  In this lesson, students will learn the basic difference between relational and non-relational databases, and how each type of database fits the diverse needs of data consumers.
- Lesson 02: Relational Data Models
  In this lesson, students understand the purpose of data modeling, the strengths and weaknesses of relational databases, and create schemas and tables in Postgres
- Lesson 03: NoSQL Data Models
  Students will understand when to use non-relational databases based on the data business needs, their strengths and weaknesses, and how to creates tables in Apache Cassandra.
- Lesson 04: Project: Data Modeling with Apache Cassandra
  Students will model event data to create a non-relational database and ETL pipeline for a music streaming app. They will define queries and tables for a database built using Apache Cassandra.
  
  Project Description - Data Modeling with Apache Cassandra
  
  Project Rubric - Data Modeling with Apache Cassandra

Part 03 : Cloud Data Warehouses with Azure

In this course, you will learn to create cloud-based data warehouses and sharpen your data warehousing skills, deepen your knowledge of data infrastructure, and be introduced to data engineering on the cloud using Azure.

Module 01:
- Lesson 01: Introduction to Cloud Data Warehouses with Azure
  In this lesson, you'll learn about the course, including the prerequisites, tools, environment, and course project.
- Lesson 02: Introduction to Data Warehouses
  In this lesson, you'll be introduced to data warehouses, ETL, and OLAP cubes.
- Lesson 03: ELT and Data Warehouse Technology in the Cloud
  In this lesson, you'll learn about ELT, the differences between ETL and ELT, and general cloud data warehouse technologies.
- Lesson 04: Azure Data Warehouse Technologies
  In this lesson, you will learn about specific data warehouse technologies and solutions in Azure.
- Lesson 05: Implementing Data Warehouses in Azure
  In this lesson, you will have the opportunity to implement a data warehouse in Azure using Synapse.
- Lesson 06: Building an Azure Data Warehouse for Bike Share Data Analytics
  In this project, you will develop a data warehouse solution using Azure Synapse Analytics to analyze bike share data.
  
  Project Description - Project: Building an Azure Data Warehouse for Bike Share Data Analytics
  
  Project Rubric - Project: Building an Azure Data Warehouse for Bike Share Data Analytics

Part 04 : Data lakes and Lakehouses with Spark and Azure Databricks

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

Module 01:
- Lesson 01: Course Introduction
  In this lesson, you'll learn about the course, including the prerequisites, tools, environment, and course project.
- Lesson 02: Big Data Ecosystem, Data Lakes, and Spark
  In this lesson, you will learn about the problems that Apache Spark is designed to solve. You'll also learn about the greater Big Data ecosystem and how Spark fits into it.
- Lesson 03: Data Wrangling with Spark
  In this lesson, we'll dive into how to use Spark for cleaning and aggregating data.
- Lesson 04: Spark Debugging and Optimization
  In this lesson, you will learn best practices for debugging and optimizing your Spark applications.
- Lesson 05: Azure Databricks
  In this lesson, you'll create Spark Clusters and Spark code on the Azure Databricks platform.
- Lesson 06: Data Lakes and Lakehouse with Azure Databricks
  In this lesson, you'll create data lakes and Lakehouse architecture on the Azure Databricks platform
- Lesson 07: Building an Azure Data Lake for Bike Share Data Analytics
  In this project, you'll implement Lakehouse architecture on the Azure Databricks platform.
  
  Project Description - Azure Data Lakehouse Project
  
  Project Rubric - Azure Data Lakehouse Project

Part 05 : Data Pipelines with Azure

In this course, you’ll learn to build, orchestrate, automate and monitor data pipelines in Azure using Azure Data Factory and pipelines in Azure Synapse Analytics. You’ll build, trigger, and monitor data pipelines on the Azure platform for analytical workloads and run data transformations, optimize data flows, and work with data pipelines in production.

Module 01: Data Pipelines with Azure
- Lesson 01: Introduction to Data Pipelines
  Welcome to Data Pipelines with Azure! In this lesson, you'll learn more about the course, including the prerequisites and tools you'll be using.
- Lesson 02: Azure Data Pipeline Components
  In this lesson, you'll learn about the components of data pipelines in Azure Data Factory and Synapse Analytics.
- Lesson 03: Transforming Data in Azure Data Pipelines
  In this lesson, you'll learn about transforming data as it moves through activities in a pipeline.
- Lesson 04: Azure Pipeline Data Quality
  In this lesson, you’ll learn about optimizing Azure Data Factory and Synapse Analytics Pipelines for data quality and integrity.
- Lesson 05: Azure Data Pipelines in Production
  In this lesson, you'll learn about features of Azure Data Factory and Synapse Analytics pipelines that you’ll use in production.
- Lesson 06: Data Integration Pipelines for NYC Payroll Data Analytics
  In this project, you'll build data pipelines for an analytics platform for the City of New York.
  
  Project Description - Data Integration Pipelines for NYC Payroll Data Analytics
  
  Project Rubric - Data Integration Pipelines for NYC Payroll Data Analytics

Part 06 : Congratulations!

Congratulations on finishing your program!

Module 01: Congratulations!
- Lesson 01: Congratulations!
  Congratulations on your graduation from this program! Please join us in celebrating your accomplishments.

**Part 07 (Career):** Career Services

The Careers team at Udacity is here to help you move forward in your career - whether it's finding a new job, exploring a new career path, or applying new skills to your current job.

Module 01:
- Lesson 01: Take 30 Min to Improve your LinkedIn
  Find your next job or connect with industry peers on LinkedIn. Ensure your profile attracts relevant leads that will grow your professional network.
  
  Project Description - Improve Your LinkedIn Profile
  
  Project Rubric - Improve Your LinkedIn Profile
- Lesson 02: Optimize Your GitHub Profile
  Other professionals are collaborating on GitHub and growing their network. Submit your profile to ensure your profile is on par with leaders in your field.
  
  Project Description - Optimize Your GitHub Profile
  
  Project Rubric - Optimize Your GitHub Profile