XBUS-518 - Data Warehouses & ETLs

School of Continuing Studies

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School of Continuing Studies

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About the course

A sound data engineering approach is the baseline by which all other data initiatives depend. Moving data through ETLs/ELTs into data warehouses that represent data in a way that is serviceable to the data goals of the organization is a critical, ongoing process to any data-driven organization. However, ETLs are filled with risks to data integrity, quality, and provenance and must be approached with best practices in mind.

This course will provide an overview of data engineering approaches and their trade offs in building different types of data warehouses. Tools for batch or stream data processing will be introduced. Common issues related to reliability, robustness, data loss, and data provenance will be explored.

This course is part of the Data Engineering track of the Advanced Data Science Certificate.

Course Objectives

Upon successful completion of the course, students will be able to:

Understand the different approaches to data warehousing across varying sized organizations.

Structure and organize data engineering initiatives.

Compose data pipelines that integrate a wide range of data tools including Python scheduling libraries or services, distributed processing systems, and multiple data stores.

Articulate the issues related to data lineage and provenance and evaluate workflow options that preserve them.

Design unit and end-to-end automated tests for data pipelines

Understand anomaly detection and alerting techniques to reinforce robust data pipelines.

XBUS-518 - Data Warehouses & ETLs at School of Continuing Studies

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Disclaimer

Coursalytics is an independent platform to find, compare, and book executive courses. Coursalytics is not endorsed by, sponsored by, or otherwise affiliated with any business school or university.

Full disclaimer.

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