This is the repository for the LinkedIn Learning course Introduction to Analytics Engineering. The full course is available from LinkedIn Learning.
Analytics engineering is a relatively new role in the field of data. If you are looking to begin a career as an analytics engineer or hire for an analytics engineering position in your company, this course can give you the information you need to get started. Instructor and analytics engineer Amataverna Lee guides you through what analytics engineering is, why it matters, and which roles can transition most easily into analytics engineering. She explains data modeling, cloud data warehouses, data pipeline tools, and business intelligence tools. Amataverna goes over several software engineering best practices. Plus, she shows you how documentation and communication are important in analytics engineering roles.
This repository has branches for each of the videos in the course. You can use the branch pop up menu in github to switch to a specific branch and take a look at the course at that stage, or you can add /tree/BRANCH_NAME to the URL to go to the branch you want to access.
The branches are structured to correspond to the videos in the course. The naming convention is CHAPTER#_MOVIE#. As an example, the branch named 02_03 corresponds to the second chapter and the third video in that chapter.
Some branches will have a beginning and an end state. These are marked with the letters b for "beginning" and e for "end". The b branch contains the code as it is at the beginning of the movie. The e branch contains the code as it is at the end of the movie. The main branch holds the final state of the code when in the course.
When switching from one exercise files branch to the next after making changes to the files, you may get a message like this:
error: Your local changes to the following files would be overwritten by checkout: [files]
Please commit your changes or stash them before you switch branches.
Aborting
To resolve this issue:
Add changes to git using this command: git add .
Commit changes using this command: git commit -m "some message"
- To use these exercise files, you must have the following installed:
- [list of requirements for course]
- Clone this repository into your local machine using the terminal (Mac), CMD (Windows), or a GUI tool like SourceTree.
- [Course-specific instructions]
Amataverna Lee
Analytics engineer
Check out my other courses on LinkedIn Learning.