The data mesh methodology calls for distributing development to data domains. Data and analytics generalists in these units rely on a shared self-service data platform and data governance standards to publish data products for local and enterprise consumption. To ensure enterprise alignment, enterprise data teams need to provide a self-service data platform that abstracts the complexity of the underlying infrastructure, making it possible for citizen developers to build data pipelines and data-driven applications without deep technical knowledge or writing code.
Data architecture as a service (DAaaS) is a new concept based on traditional best practices. DAaaS embeds enterprise standards and know-how into point-and-click development tools geared. This gives domain developers the best of all worlds: the freedom and agility to build their own data-driven solutions while adhering to enterprise standards and best practices. The result is the data domains build solutions quickly and efficiently without creating data silos that undermine enterprise data consistency. The webinar will examine the convergence of data mesh and DAaaS and demonstrate DAaaS-enabled tools in action.
You Will Learn:
• How DAaaS helps fulfill the promise of data mesh
• Best practices to create a self-service data mesh platform that abstracts complexity
• How DAaaS embeds standard rules and best practices into self-service tools
• Why data mesh requires data architecture as a service (DAaaS)
Sponsor: Coalesce
