This article introduces Data Product Portfolio Management (DPPM), a critical capability for implementing sustainable data mesh architectures. It uses three nature-based analogies—Kudzu (uncontrolled growth), Desert (over-governance), and Bonsai (balanced cultivation)—to illustrate the challenges and best practices.

• DPPM protects organizational value by measuring data product contributions to business goals
• DPPM manages risk from unmanaged data products and ensures quality oversight
• DPPM guides evolution of data landscapes toward organizational data strategy goals
• Key roles include CDO, domain architects, data owners, stewards, and product owners
• Strategic practices: strategy development, methodology development, optimal portfolio selection
• Tactical practices: portfolio adjustment, data product proposals, methodology selection
• Operational practices: pre-screening, analysis, screening, development, decommissioning, evaluation
• Data products classified as trunk (core), branch (cross-domain), or leaf (specialized)
• Value and risk driven by consumer use cases, not inherent to products themselves
• Technology enablers: data catalogs, service management tools, demand management solutions

DPPM provides a structured framework to balance innovation with governance, preventing both chaotic proliferation and restrictive stagnation in data mesh implementations.