Over the past 20 to 30 years the practices of architectural data management have focused primarily on analytical data – architecture for data warehousing and data lakes. Throughout those years, Operational Data Architecture has been largely neglected while the scope, variety, and complexity of operational systems and operational data have expanded substantial.

The operational data landscape – once composed predominantly of transactional systems – now includes automation and IoT systems, as well as, transactional applications. Transactional systems of the past were primarily developed internally with some attention to consistency and connectedness among systems. Today’s operational data landscape includes legacy, ERP, SaaS, and custom applications. Operational data platforms encompass mainframe, on-premises servers, cloud, multi-cloud, and mobile devices. This 5-hour, 22-minute course focuses on understanding today’s operational data landscape – an essential first step toward modernizing operational data architecture and operational data management.

• History and evolution of operational systems
• The variety of operational systems and the roles of each
• The similarities and differences of Data Lake, Data Fabric, and Data Mesh architectures
• The variety of operational data platforms and the characteristics of each
• The variety of data created and managed by operational systems
• Implications of global data variations and mobile data variations
• The roles of MDM and RDM in operational data management

• Current and aspiring data architects
• Data scientists and data engineers
• Data warehousing and data lake designers and developers
• Data and information systems program and project managers