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--- data-mesh [2024-09-13 08:55] – mrks
+++ data-mesh [2025-01-13 11:59] (current) – mrks
@@ Line 74: / Line 74: @@
   * Data products must **interoperate to get value in forms of higher order datasets and insights**
+===== Designing data products =====
+[[https://martinfowler.com/articles/designing-data-products.html|Designing data products – Kiran Prakash (2024-12-10 martinfowler.com)]]
+  * "Data products **package structured, semi-structured or unstructured analytical data for effective consumption** and data driven decision making, keeping in mind specific user groups and their consumption pattern for these analytical data."
+  * "One of the most prevalent misunderstandings is **conflating data products with data-driven applications**. Data products are natively **designed for programmatic access and composability**, whereas data-driven applications are primarily intended for human interaction and are not inherently composable."
+  * "**No single data product should be owned by multiple domains**, as this can lead to confusion and finger-pointing over quality issues."
+  * "While it's important to consider domain ownership early, **it’s often more efficient to have a single team develop all the necessary data products** to realise the use case at the start of your data mesh journey. Splitting the work among multiple teams too early can increase coordination overhead, which is best delayed. Our recommendation is to begin with a small, cohesive team that handles all data products for the use case. As you progress, use “team cognitive load” as a guide for when to split into specific domain teams."
+  * "**Having a consistent blueprints for all data products will make this transition of ownership easier when the time comes**. The new team can focus solely on the business logic encapsulated within the data products, while the organization-wide knowledge of how data products are built and operated is carried forward."
+  * "**For structured data, this usually means a single denormalized table**, and for semi-structured or unstructured data, a single dataset. Anything larger is likely trying to do too much, making it harder to explain its purpose in a clear, concise sentence and reducing its composability and reusability."
+  * "In our experience, **it's beneficial for each data product identified earlier to have its own source control repository and associated deployment pipeline**, allowing for independent management of its lifecycle."