You need to recommend a strategy to consistently define the business unit, department, and product category data and make the data usable across reports.
I feel like using a single shared dataset for every report might lead to issues if the data changes frequently. It seems risky, but it could simplify things.
I think creating dataflows could be a good option since it allows for centralized management of standardized data, but I need to double-check how that integrates with reports.
For the three entities, I think creating exports of the data from the Power BI model to Excel and storing the data in Microsoft OneDrive for others to use as a source could be a good option. That way, we can make the data easily accessible to everyone who needs it.
Creating and using a single shared dataset that contains the standardized data for every report seems like the most straightforward solution. That way, we can be sure that everyone is using the same data source.
Hmm, I'm a bit unsure about this one. Creating a shared dataset for each standardized entity seems like it could work, but I'm not sure if that's the most efficient approach. I'll need to think this through a bit more.
I think the best approach here is to create dataflows for the standardized data and make them available for use in all imported datasets. That way, we can ensure consistency across reports without having to recreate the same data in multiple places.
I'm feeling option A. A shared dataset for each standardized entity is straightforward and easy to understand. Plus, it's probably the most secure option, right?
Option D is interesting, but I'm not sure storing the data in OneDrive is the best idea. What if someone accidentally deletes it or makes unauthorized changes? I'd stick with a more centralized solution.
Hmm, option C looks good to me. Having a single shared dataset with the standardized data for all reports sounds like it would make things really easy to manage.
I think option B is the way to go. Creating dataflows for the standardized data and making them available for all imported datasets seems like the most efficient and scalable approach.
Karl
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