In 2019, ‪Zhamak Dehghani‪ published a thought-provoking article highlighting common failure modes of centralized data architectures and advocated instead for a decentralized, domain-oriented approach in which data is managed as a product.  This paradigm is described as a Data Mesh and it builds upon prior architectural concepts such as microservices, domain bounded contexts and elastic platform infrastructure solutions that unlock scalability.  In this talk, we will discuss how Data Mesh can be applied by organizations that are looking to expand their product offerings, perhaps even through growth strategies that include mergers and acquisitions.  If you are struggling to derive value from your organization’s data due to overly complex and coupled ETL pipelines or monolithic big data stores, Data Mesh will likely be a refreshing new take that intuitively resonates with teams who need agility in managing, serving and composing novel insights from their product offerings.  Additionally, if you are leading development teams, Data Mesh can provide the missing blueprint that allows you to escape an org chart in which data engineers are siloed from the subject matters experts who can best articulate how your organization’s data can be utilized to great effect.