Data management involves a variety of processes and practices to collect, organize, store, and deliver high-quality data for data science, business intelligence, performance management, and business operations. Data engineering is an essential discipline that is responsible to design, build, and deploy data management capabilities. The data engineering discipline encompasses three distinct roles: database engineer, data pipeline engineer, and data product engineer.

This course focuses on the role of data product engineer – the technical professional who designs, builds, and deploys data products for data delivery, data sharing, data integration, and data interoperability. The data product engineering skill set includes requirements analysis, data modeling, data product design, API modeling and design, metadata management, data contracts, and data services. Data products combine software, data, and metadata for many purposes: serving data, data validation, quality assurance, transformation, aggregation, composition, profiling, and more. The range of data product platforms and technologies is as broad and diverse as the variety of data products that are possible.

On completion of this course you will have a solid foundation of knowledge and skills needed for data product engineering.

• What are Data Products?
• What is Data Product Engineering?
• The Data Product Engineering Process
• Components of Products
• Characteristics of Data Products
• API concepts, standards, practices, and design patterns
• The role of data contracts and service level agreements for Data Products
• Data Product Deployment, Orchestration, and Operation

• Data Engineers
• Data Architects
• Data Scientists
• Data Analysts
• DevOps Engineers
• IT Professionals
• Data Warehousing Specialists
• ETL Developers
• Big Data Engineers