Companies rely on modern cloud data architectures to transform their organizations into the agile analytics-driven cultures needed to be competitive and resilient. The modern cloud reference architecture applies data architecture principles into cloud platforms with current database and analytics technologies. However, many organizations quickly get in over their head without a carefully prioritized and actionable roadmap aligned with business initiatives and priorities. Building such a roadmap follows a step-by-step process that produces a valuable communication tool for everyone to deliver together.
This session will cover the four significant steps to align the data strategy and roadmap with the business. We’ll start with translating business strategy into data and analytics strategies with the Enterprise Analytics Capabilities Framework. This is followed with a logical modern cloud reference data architecture that can leverage agile architecture techniques for implementation as a modern data infrastructure on any cloud, hybrid or multi-cloud environment. This will provide the basis for drilling deeper into architecture patterns and developing proficiency with DataOps and MLOps.
This session will cover:
- How to identify and translate business priorities into analytic capabilities
- How the Enterprise Analytics Capabilities Framework guides architecture roadmaps
- Modern data architecture components: data lake, DW, data hubs, and sandboxes
- Modern architecture patterns: polyglot persistence, data lakehouse, data fabric, data mesh
- Modern integration architecture components: ingestion, data pipelines, event streaming
- Modern data infrastructure on AWS, Azure, and GCP.