Nanodegree Program
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.
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.
Advanced
2 months
Last Updated September 13, 2024
Skills you'll learn:
Prerequisites:
Course 1 • 45 minutes
Welcome to Udacity! We're excited to share more about your Nanodegree program and start this journey with you!
Lesson 1
Welcome to Udacity. Takes 5 minutes to get familiar with Udacity courses and gain some tips to succeed in courses.
Lesson 2
You are starting a challenging but rewarding journey! Take 5 minutes to read how to get help with projects and content.
Course 2 • 2 weeks
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.
Lesson 1
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 2
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 3
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 4 • Project
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.
Course 3 • 3 weeks
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.
Lesson 1
In this lesson, you'll learn about the course, including the prerequisites, tools, environment, and course project.
Lesson 2
In this lesson, you'll be introduced to data warehouses, ETL, and OLAP cubes.
Lesson 3
In this lesson, you'll learn about ELT, the differences between ETL and ELT, and general cloud data warehouse technologies.
Lesson 4
In this lesson, you will learn about specific data warehouse technologies and solutions in Azure.
Lesson 5
In this lesson, you will have the opportunity to implement a data warehouse in Azure using Synapse.
Lesson 6 • Project
In this project, you will develop a data warehouse solution using Azure Synapse Analytics to analyze bike share data.
Course 4 • 3 weeks
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.
Lesson 1
In this lesson, you'll learn about the course, including the prerequisites, tools, environment, and course project.
Lesson 2
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 3
In this lesson, we'll dive into how to use Spark for cleaning and aggregating data.
Lesson 4
In this lesson, you will learn best practices for debugging and optimizing your Spark applications.
Lesson 5
In this lesson, you'll create Spark Clusters and Spark code on the Azure Databricks platform.
Lesson 6
In this lesson, you'll create data lakes and Lakehouse architecture on the Azure Databricks platform
Lesson 7 • Project
In this project, you'll implement Lakehouse architecture on the Azure Databricks platform.
Sr. Cloud Solution Architect at Microsoft
Lucky is a data & AI evangelist with a track record of successfully helping organizations build analytics solutions. Besides his day job, he teaches as an adjunct professor, delivers lunch & learns, mentors students, and evangelizes Azure Quantum as an ambassador.
Developer Advocate at DataStax
Amanda is a developer advocate for DataStax after spending the last 6 years as a software engineer on 4 different distributed databases. Her passion is bridging the gap between customers and engineering. She has degrees from the University of Washington and Santa Clara University.
Data Science Practice Lead at Cognitell
Matt is a data science professional whose career has spanned software development, user experience design, and data visualization. He earned his PhD in the research area of cognitive psychology in human learning and is an adjunct professor teaching software design courses.
Average Rating: 4.3 Stars
3 Reviews
Alvaro F.
November 29, 2022
It went really well. It's easy to follow the steps and lear. The experience with the platform could be better though.
Obinna Ezinwa O.
October 22, 2022
the videos are easy to understand. project review helps to clarify questions
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