Data Modeling, Transformation, and Serving

In this course, you’ll model, transform, and serve data for both analytics and machine learning use cases. You’ll explore various data modeling techniques for batch analytics, including normalization, star schema, data vault, and one big table, and you’ll use dbt to transform a dataset based on a star schema and one big table. You’ll also compare the Inmon vs Kimball data modeling approaches for data warehouses. You’ll model and transform a tabular dataset for machine learning purposes. You’ll a

• Model and transform data based on stakeholder needs to deliver business value
• Choose the appropriate data processing tools for your architecture design
• Process data for batch analytics and machine learning data pipelines using distributed and non-distributed processing frameworks