- Please note that this course has the following prerequisites which must be completed before it can be accessed
- Introduction to Machine Learning for Data Science
- Artificial Intelligence & Machine Learning
About This Course
In this course, I take you from the fundamentals and concepts of data modeling all the way through a number of best practices and techniques that you’ll need to build data models in your organization. You’ll find many examples that clearly demonstrate the key concepts and techniques covered throughout the course.
By the end of the course, you’ll be all set to not only put these principles to work, but also to make the key data modeling and design decisions required by the “art” of data modeling that transcend the nuts-and-bolts techniques and design patterns.
Organisations, or groups of organisations, may establish the need for master data management when they hold more than one copy of data about a business entity. Holding more than one copy of this master data inherently means that there is an inefficiency in maintaining a “single version of the truth” across all copies. Unless people, processes and technology are in place to ensure that the data values are kept aligned across all copies, it is almost inevitable that different versions of information about a business entity will be held.
- Basic understanding of data management concepts and constructs such as relational database tables
- Know how different pieces of data logically relate to one another.
- A business analyst
- Data engineer, or database designer
- Who desires to build a personal toolbox of data modeling best practices and techniques.
Apply the principles