Christine Harney

A hands-on program that provides foundational knowledge and skills for designing, creating, and consuming data products using DataOS. Through guided exercises and practical examples, participants will gain an introductory understanding of building scalable, reusable data products, managing governance policies, and leveraging DataOS to enable enterprise-wide data-driven decision-making. This program is an excellent starting point for teams looking to adopt DataOS and establish a strong base for more advanced training and certification.

Target Audience

Required for:
Data Developers, Data Engineers, Data Product Developers, Data Product Owners
- These roles rely on this foundational knowledge to progress into specialized tracks.

Recommended for:
Technical Leads, App Developers, DataOS Admins
- These participants benefit from a shared understanding of core concepts, terminology, and data product lifecycle principles in DataOS.

Duration: 12 hours

Learning Objectives

1. Understand Data as a Product: Learn the principles of treating data as a product, including its lifecycle and impact on business outcomes.
2. Design Data Products: Learn the principles of source-aligned and consumer-aligned data product design, aligning business needs with data architecture.
3. Create and Consume Data Products: Build data products using workflows & services, query data for analytics, and deliver standardized outputs for business use cases.
4. Ensure Data Integrity and Quality: Master the foundational principles of metadata generation and lineage tracking in DataOS, ensuring trust and accountability in your data products.

Key Learnings

Upon completing this training, participants will be equipped to build and manage data products in DataOS, aligned with enterprise data strategies. They will gain hands-on experience in governance, metadata management, and access control, using DataOS to design scalable workflows. This training also lays a strong foundation for advanced learning paths, including Data Product Developer and Data Product Owner.