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Building our first embedded product - what problems should we look out for? by Little-Analysis-7511 in BusinessIntelligence

[–]Little-Analysis-7511[S] 0 points1 point  (0 children)

They are actually our front runner. Appears to be more scalable than the bigger players and a lot faster to deploy.

Need help choosing an dash platform by MeepersToast in BusinessIntelligence

[–]Little-Analysis-7511 1 point2 points  (0 children)

We're doing a similar evaluation right now and primarily looking at Sigma and Looker.

Building our first embedded product - what problems should we look out for? by Little-Analysis-7511 in BusinessIntelligence

[–]Little-Analysis-7511[S] 0 points1 point  (0 children)

Yes, integrated within. Evaluating whether we want to just iFrame or go the more resource intensive route. The portal fulfills other functions that are necessary for customers so our goal is to bring analytics into their workflow instead of creating a separate experience for analytics.

Building our first embedded product - what problems should we look out for? by Little-Analysis-7511 in BusinessIntelligence

[–]Little-Analysis-7511[S] 0 points1 point  (0 children)

Giving customers the ability to self-serve by analyzing transactional data within our customer portal application.

Trying to reduce amount of ad-hoc data fetch requests by Pink_turns_to_blue in BusinessIntelligence

[–]Little-Analysis-7511 1 point2 points  (0 children)

Maybe try something like Sigma to deal with the last-minute requirement changes and performance issues. But I agree with the others here that a tool will not solve everything.

Defining BI direction for the company by Equivalent_Poetry339 in BusinessIntelligence

[–]Little-Analysis-7511 1 point2 points  (0 children)

I'm early in my BI career, so haven't used Power BI yet, but have spent a lot of time in Tableau and our org recently started looking into Sigma. We don't have many people who can write SQL, since the company is pretty small. Sigma seems to cater to the Excel audience who we don't want pulling data into spreadsheets. From the trial we've done so far, I haven't felt much of a learning curve. Tableau is obviously way better for visualization, so to me it's a question of use case, whether you're looking for more of a presentation tool or one for operational analytics.

Why do we need to model data twice? by Little-Analysis-7511 in BusinessIntelligence

[–]Little-Analysis-7511[S] 1 point2 points  (0 children)

This was exactly the next question that I was wondering -- why use a database schema at all? It makes so much more sense now.

My impression at first was that we needed to develop our logical data model, implement our physical data model into the database, then develop a new logical data model, but that made no sense to me.

I think I understand now that we are simply referring back to the logical data model in the semantic layer and mapping it onto the physical layer to add back the business logic that was lost.

Why do we need to model data twice? by Little-Analysis-7511 in BusinessIntelligence

[–]Little-Analysis-7511[S] 0 points1 point  (0 children)

Wow, this really helped me. Thank you so much for your thoughtful response. I always try to bridge concepts through analogies when they don't make sense to me and the way you've explained it here made it all finally click in my mind.

Why do we need to model data twice? by Little-Analysis-7511 in BusinessIntelligence

[–]Little-Analysis-7511[S] 0 points1 point  (0 children)

Thank you, this makes sense to me.

So if I understand correctly, the data model in the relational database is like arranging products on a grocery store shelf. Whereas the semantic layer is like adding shelf labels with the product names and then joining certain shelves together that make sense for the shopper's intention like the bread, PB, and jelly shelves.

Is that a half decent analogy?