This course is designed for business and data professional seeking to learn the first technical phase of the data science process known as Extract, Transform and Load or ETL.
Learners will be taught how to collect data from multiple sources so it is available to be transformed and cleaned and then will dive into collected data sets to prepare and clean data so that it can later be loaded into its ultimate destination. In the conclusion of the course learners will load data into its ultimate destination so that it can be analyzed and modeled.
The typical student in this course will have experience working with data and aptitude with computer programming.
Overview
Syllabus
- Extract Data
- The first truly hands-on technical phase of the data science process is actually a combination of related tasks known as extract, transform, and load (ETL). This is where you, the data science practitioner, start to mold and shape the data so that it can be as useful as possible for the later steps in the data science process. In this course, you'll go through each ETL task in order, starting with "E" (extract).
- Transform Data
- The next step in the ETL process is transformation. You'll spend this next module adjusting your data so that it's in a more useful state.
- Load Data
- The last step in the ETL process is loading. In this module, you'll take the data you transformed and put it into a destination format and location, where it will be ready for you to work on as the project progresses.
- Apply What You've Learned
- You'll work on a project in which you'll apply your knowledge of the material in this course to a practical scenario.
Taught by
Stacey McBrine, Sarah Haq and Megan Smith Branch
