Right definition for a product and related functionalities about a data solution/project
in order to implement a data solution/project to deliver a data warehouse, I'd like better understanding the definitions for the corresponding product and the related functionalities. I can use Azure DevOps.
A data solution is different respect to a software solution. A possible data solution could be to implement a data warehouse to feed from some data sources; a possible software solution could be to implement a company web site.
I'm trying to define the (final) product to deliver for the above data solution: I think it is the data warehouse, but it is less tangible "object" than a company web site for an end user.
Respect to the data warehouse as a product, which could it be a related functionality (to deliver)? Can I consider the "design of a staging area" or "staging area" as a feature? In the first case I could have the "design of a staging area" and the "creation of a staging area" as a feature, in the second scenario I could have the "staging area" as a feature to explode, f.e., in the "design" and "creation" and "data ingestion" pbis.
Moreover, for a data solution/project when I think to a deliverable "object" I could say a technical document, an architecture schema, a staging area (that is a data structure), and not only an ETL that runs a data ingestion. For a company web site, the product is the web site and a possible functionality could be a contact page that represents a more tangible "object" whereby an end user could interact.
Any helps to better understanding the product and functionality definition for a data project?
Does it exist any articles to handle how applying Scrum for a data solution?
Who wants that data solution, and how can you experimentally and empirically verify that it meets human needs?
If that data solution "project" has been conceived of and sanctioned without considering this angle, there's a problem. Human beings are complex. Most of a system's complexity is likely to come down to people and how they behave. The complexity we manage in Scrum, Sprint by Sprint, is rather less likely to be due to the vagaries of a technology stack or platform.
I'm struggling to understand your concern. A data solution is just another complex problem to solve. But it should have some defined stakeholder needs. Those needs to be captured in a way that can be understood by the stakeholders and the technical team that will be providing the solution. What you are talking about is the actual architecture of the product. That should be determined by the Developers. If they need to create documentation, then they can. But it isn't something that is captured in the product description. That documentation supports the product structure.
In Scrum and most other agile practices, the architecture evolves as the solution is created. Capturing the needs of the stakeholders is the most important part, because that defines the complexity needed to create a solution.
Hi, thanks for your replies.
I'm a beginner about Scrum. I'm trying to explain better the question.
I need to implement a data management solution that could say as a data management project. The goal of this solution is to implement a data warehouse, by migrating the existing one, as required from my customer.
I've already detected more activities in order to deliver a data warehouse, and I could achieve this delivery without applying a such framework. But I should follow Scrum, and so I'd like to understand better some concepts by referring a data management solution to deliver a data warehouse.
Now, any helps to better understanding the product and functionality definition for a data management solution?
Does it exist any articles to handle how applying Scrum for a data management solution?
I could define the data warehouse to deliver as a product following Scrum, isn'it?
About the functionality definition?
I need to indicate in an Azure DevOps installation which are the features, which are the product backlog items and so on.