Enroll Course: https://www.coursera.org/learn/data-modeling-transformation-serving
In today’s data-driven world, understanding how to effectively model, transform, and serve data is crucial for analytics and machine learning projects. The Coursera course titled “Data Modeling, Transformation, and Serving” offers an in-depth exploration of these fundamental skills. This course is perfect for data professionals looking to enhance their data architecture knowledge or for those aiming to implement robust data pipelines for various use cases.
The course covers a wide array of data modeling techniques suitable for batch analytics, including normalization, star schema, data vault, and the concept of a single large table. A significant portion of the course emphasizes practical application through the use of dbt (data build tool), where students learn to transform datasets based on a star schema and a big table approach. Additionally, the course provides a detailed comparison of the Inmon and Kimball methodologies for data warehousing—an essential component for any enterprise data architecture.
Beyond analytics, the course emphasizes modeling and transforming data specifically for machine learning purposes, teaching students how to prepare data for predictive models effectively. The syllabus also covers critical technical considerations during data transformations and best practices for serving data efficiently to downstream applications.
I highly recommend this course for data engineers, analysts, and data scientists seeking to deepen their understanding of data modeling and transformation techniques. The combination of theoretical knowledge and practical exercises using real-world tools like dbt makes it an invaluable resource. Enroll today to strengthen your data foundational skills and elevate your data projects to the next level.
Enroll Course: https://www.coursera.org/learn/data-modeling-transformation-serving