Platform Oriented Data Architecture for Accelerated Insights

To embrace productive data architecture, many organizations introduce centralized data lake fed by operational data stores and data streams. However, that solution introduces problems of quality, governance, and delayed access. This hampers the agility as the consumers such as ML and AI teams deal with inferior quality data which are difficult to use and combine due to the lack of standards and governance. Recently, a new form of data architecture appeared, which is centered around the intersection of platforms, domains, and data.  In this approach, influenced by Domain-Driven Design (DDD), the team that owns the domain owns the operational stores but also the domain specific area of the data lake, and they handle quality and governance of the data in their area – resulting in a Data Product. The result is that consumers can rapidly combine high-quality data from various sources and put them together, resulting in accelerated insights. We will discuss the architectural, organizational, and technical underpinnings of Platform Oriented Data Architecture, based on the set of common data infrastructure services.