❗The content presented here is sourced directly from Youtube platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [May 30th, 2023]

What does this course tell?
(Please note that the following overview content is from the original platform)


- Welcome.
- Learning objectives​ and introduction.
- Denormalize data in your model​.
- Manage referential integrity by using change feed​.
- Combine multiple entities in the same container​.
- Denormalize aggregates in the same container​.
- Finalize the data model​.
- Exercise​: Exercise advanced modeling patterns​.
- Knowledge Check​.
- Summary​ and conclusion
.


We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
Welcome to Learn Live - Design a data partitioning strategy! In this course, you will learn how to design a data partitioning strategy for your data model. You will learn how to denormalize data in your model, manage referential integrity by using change feed, combine multiple entities in the same container, denormalize aggregates in the same container, and finalize the data model. You will also have the opportunity to practice advanced modeling patterns through an exercise. At the end of the course, you will have a knowledge check to assess your understanding of the material.

By taking this course, you will gain the skills and knowledge necessary to design a data partitioning strategy for your data model. This will help you to better organize and manage your data, and make it easier to access and analyze. Additionally, this course will provide you with the opportunity to develop your skills in data modeling and data partitioning, which can be beneficial for your career or education. You can use these skills to develop data-driven applications, or to pursue further studies in data science or related fields. Furthermore, this course can also provide you with the opportunity to learn more about data management and data analysis, which can be useful for any job or project.