I wonder if this makes BI companies freak out a little bit -- because pushing this data into redshift and adding a visualization layer on top takes care of most smaller scale BI needs...
The T, transformation, is huge in many ways. Think of it this way: the data model is the primary UI for an analyst or any power user. It also dictates query performance.
Adding a visualization layer on top of Salesforce's schema, e.g. is not too helpful, regardless of where that data is living. You can answer trivial questions without too much difficulty, but the difficulty ramps up quickly.
The data access patterns, types of logic necessary, and end-user demands are hugely different between an OLTP and OLAP workload.
There's also potentially huge complexity in conforming dimensions across disparate source systems' data.
Master data management is another huge component that hits a lot of the ETL pipeline.
These concerns are all on top of hooking up the right ends of the hose to one another.
I don't mean to disparage the product or company and hope I don't come across as if I am. I just want to point out that they address only a small component of a large process, which in turn is only a segment of the BI lifecycle.
We at Looker (disclosure: work there), are totally focused on making the transformations fast, flexible and powerful. But without the data to transform, there's nothing we can do to help customers. So we're super psyched that Segment is stepping in to fill this void and get the E and L done, so we can T.
Tools like Segment and yours are invaluable. I work for a Microsoft partner, so often am stuck in that ecosystem for better or worse, but the problems and solutions in the BI space are largely universal and transcend specific tools. Even when the tools make individual tasks trivial, the overall architecture and design of a data pipeline and visualization solution leave plenty of room for companies like the one I work for.
This product release is in close partnership with our BI partners (Looker, Mode, Wagon, Periscope, BIME and Chartio). One of the biggest problems our mutual customers face is getting data into their warehouse so that they can use the BI tool in the first place. This launch significantly expands the possible audience for them.
Even better, all of our BI partners built out-of-the-box reporting and dashboards based on Segment's schemas for these new third party sources. So our mutual customers can get set up even faster.
There are other ways to load in Salesforce, Zendesk, or Stripe data. It is certainly nice to be able to do that all with Segment -- but it is not necessary. Sources is nice to have, but the core warehouse service is not really complete (for us, and I suspect others too) until you can seamlessly support data backfill at all price tiers. A one-time fee for backfill fee would be okay, but saying "no we don't support that" makes me sad.
Maybe you are estimating data size based on known types of data in salesforce,zendesk,etc. But what if i want to load data from my internal dB as well? The 60 day notions,etc.
So, instead of Total Company Sales this Month, I want Bob's Sales, Joe's Sales, etc. It feels like this is just a filter on top of what you already have. Almost like a parameterized query? (pass in @UserId for a where statement)
I originally thought maybe this is the job for one of your visualization partners but you really need to filter the results before you perform the aggregate.
Our salesforce source pulls in the Salesforce `Opportunities` and `Users` table (your sales team members). So to get sales by sales rep, you can join the `Opportunities` table to `Users` table, and then aggregate by sales rep.
Once you get the raw data into your data warehouse, you have a ton of flexibility with how you aggregate and analyze it.
I can't tell you how many potential customers are crazily excited about the idea of centralizing the data that all their apps produce into one central warehouse and putting Looker on top of that, but are stymied by the middle step of actually getting the data OUT of the vendors' APIs and IN to their own warehouse. Being able to point them to an off-the-shelf solution for that problem is a big win for us.