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Nicholas DeGiacomo, Shrinath Parikh, Rostislav Rabotnik, Vijaya Nelavelli, Shankar Korrapolu, and Ben Larson

Discover Data Architecture foundations. Enroll in our comprehensive online training course. Master the principles with expert-led guidance. Start today!

Prerequisite details

Read more

Discover Data Architecture foundations. Enroll in our comprehensive online training course. Master the principles with expert-led guidance. Start today!

Prerequisite details

To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:

  • Intermediate SQL
  • Relational database basics

You will also need to be able to communicate fluently and professionally in written and spoken English.

What's inside

Syllabus

This is the welcome lesson of the course.
This lesson will cover basic data architecture characteristics, data governance and business requirements.
Read more
This lesson will cover model, schema and normalization
This lesson will cover conceptual, logical and physical ERD, and how to create ERDs
This lesson will cover how to create and populate a database and run CRUD command
Architect a database based on the business requirements for a Human Resources Department, combining all the skills you've learned so far!

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops schemas and ERDs, which are core skills for data architects
Examines data governance and business requirements, which are highly relevant to data architecture
Taught by Nicholas DeGiacomo, Shrinath Parikh, Rostislav Rabotnik, Vijaya Nelavelli, Shankar Korrapolu, and Ben Larson, who are recognized for their work in data architecture
Offered through Udacity, which is recognized for its work in online education
Includes hands-on labs and interactive materials for practical application

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Architecture Foundations with these activities:
Read Data Warehouse System Concepts
Gain a thorough understanding of data warehouse system concepts to enhance your learning in this course.
Show steps
  • Read the chapters related to data modeling, data warehousing, and data analysis
  • Take notes and highlight important concepts
Review SQL Queries
Familiarize yourself with SQL queries before the course starts to make learning data architecture easier.
Browse courses on SQL
Show steps
  • Review basic SQL syntax and commands
  • Practice writing SQL queries to retrieve and manipulate data
  • Use an online SQL editor or download a database management system to practice
Seek Mentorship from Data Architecture Experts
Connect with experienced data architecture professionals to gain valuable guidance and insights.
Show steps
  • Identify potential mentors through online forums, LinkedIn, or industry events
  • Reach out to mentors and express your interest in learning from their experience
  • Schedule regular meetings to discuss data architecture concepts and best practices
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow Tutorials on Data Normalization
Enhance your understanding of data normalization techniques through guided tutorials.
Show steps
  • Search for online tutorials on data normalization
  • Follow the tutorials to learn about different normalization forms
  • Practice applying normalization techniques to sample datasets
Design a Database Schema for a Small Business
Apply your knowledge of data architecture to create a database schema for a real-world scenario.
Show steps
  • Gather requirements from a small business owner
  • Create an entity-relationship diagram (ERD) to model the business's data
  • Design a relational database schema based on the ERD
  • Implement the database schema using a database management system
Develop an ERD for a Real-World Use Case
Reinforce your understanding of ERDs by creating one for a real-world use case.
Show steps
  • Choose a real-world business process or scenario
  • Identify the entities, relationships, and attributes involved
  • Create an ERD using a modeling tool or software
  • Validate your ERD by sharing it with peers or instructors for feedback
Practice SQL CRUD Operations
Improve your proficiency in SQL CRUD operations to enhance your data manipulation skills.
Show steps
  • Set up a practice database with sample tables
  • Perform CRUD operations (Create, Read, Update, Delete) using SQL queries
  • Troubleshoot errors or issues encountered during practice
Volunteer at a Non-Profit Organization
Gain practical experience in data management while contributing to a meaningful cause.
Show steps
  • Identify a non-profit organization that needs data support
  • Offer your assistance with data organization, analysis, or reporting
  • Apply your knowledge and skills to real-world data challenges

Career center

Learners who complete Data Architecture Foundations will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 11 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Architecture Foundations.
Classic guide to dimensional modeling, a widely used technique for designing data warehouses. It valuable resource for anyone who wants to learn more about dimensional modeling or improve their data warehousing skills.
Provides a comprehensive overview of big data, covering the principles and best practices of scalable real-time data systems. It valuable resource for anyone who wants to learn more about big data or improve their big data skills.
Comprehensive guide to Hadoop, the open-source framework for big data processing. It valuable resource for anyone who wants to learn more about Hadoop or improve their Hadoop skills.
Comprehensive guide to Spark, the open-source framework for big data processing. It valuable resource for anyone who wants to learn more about Spark or improve their Spark skills.
Provides a comprehensive overview of deep learning with Python, a popular programming language for deep learning. It valuable resource for anyone who wants to learn more about deep learning or improve their deep learning skills.
Provides a comprehensive overview of Keras, a high-level neural networks API, written in Python and capable of running on top of TensorFlow or Theano. It valuable resource for anyone who wants to learn more about Keras or improve their Keras skills.
Provides a comprehensive overview of natural language processing with Python, a popular programming language for natural language processing. It valuable resource for anyone who wants to learn more about natural language processing or improve their natural language processing skills.
Provides a comprehensive overview of computer vision with OpenCV, a popular open-source library for computer vision. It valuable resource for anyone who wants to learn more about computer vision or improve their computer vision skills.
Provides a comprehensive overview of machine learning with Scikit-Learn, Keras, and TensorFlow, three popular open-source libraries for machine learning. It valuable resource for anyone who wants to learn more about machine learning or improve their machine learning skills.
Provides a comprehensive overview of reinforcement learning, a type of machine learning that allows agents to learn how to behave in an environment by interacting with it. It valuable resource for anyone who wants to learn more about reinforcement learning or improve their reinforcement learning skills.

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