Yet more Gemini demos dissected

Some more Gemini demos have appeared on the BI Blog, with more new Gemini features revealed, so let’s step through them and see what we can see…

• 2:45 Nothing much so far we haven’t seen already. However the toolbars are much easier to see in this video and the first thing pointed out is the list of tables loaded into Gemini listed at the bottom of the screen.
• 3:15 We can also see a lot more of the toolbar at the top here too. In the ribbon we can see the following areas:
• New Table, with buttons to import new tables from a database or from the clipboard
• Table Tools, with buttons to create relationships between tables and to manage relationships. So far I’m getting a very strong feeling of relational database concepts coming through – ok if the Gemini user is familiar with them (perhaps through Access), but is it asking too much of a user to think in terms of tables and joins?
• Columns Tools. Can’t see much here, but we saw a bit earlier in the demo that on the far right hand side of the data area it seems you can add new columns onto the end of the table, and the buttons here allow you to manage these columns, delete them, resize them etc.
• Sort and Filter, pretty much self-explanatory
• Calculations. Again can’t see much here, but the button at the top says Manual. I wonder if it’s going to give you the option to either automatically apply all your calculations, or only apply them when you press a button (in case calculation takes a long time).
• View. The options here are Pivot Table and Switch to Excel. I guess the demo is done in some kind of Table view, and we’ll have the option to view the data instead in a pivot table or go to Excel and work with the data there in the way we would with any other external data source.
• 4:17 The now inevitable OOHHH moment in a Gemini demo where we see 20 million rows of data being manipulated in memory. Of course, though, the amount of data we can work with will not only depend on how much memory we have but also how well it can be compressed. From what I understand of COP databases like Gemini, you get great compression because it only stores the distinct values held in each column; but if your data contains a lot of different values then you won’t be able to compress it as much and you won’t be able to work with as much of it. I think.
• 4:46 And not wishing to sound like Mr Sceptical, but watching all these demos of sorting and filtering large amounts of data very quickly raises a question in my mind: are all the rows in the table actually sorted and filtered, or does Gemini just do enough sorting and filtering to fill the screen? Finding the top 30 or so rows out of 20 million based on a value is certainly impressive, but it’s not the same as sorting all those 20 million rows.
• 6:23 The Manage Relationships dialog. Again, very relational and strangely non-visual as well; I’d have expected a graphical representation of the two tables joined, just like you’d get in any other database tool. Maybe it’s not ready yet though.
• 6:55 Looks like our first sight of DAX. The expression is:
  sumx(RELATEDTABLE(Purchase), Purchase[PurchaseSourceId])
  Hmm, again seems more like a SQL expression (a sum/inner join) translated to Excel rather than anything resembling MDX. It does the calculation very quickly although it’s the first time something has been less than instant.

• 0:25 We’re in Excel now, using a pivot table, but notice that on the right-hand side we have the ‘Gemini task pane’ so perhaps it’s not a regular pivot table?
• 2:48 Create Relationship dialog. Again it doesn’t seem very graphical, and notice the use of relational database terminology again with the mention of primary keys and foreign keys; for someone who is used to working with databases this is fine, the obvious term to use, but are these concepts we should expect Gemini users to understand? Shouldn’t things be less technical, more user friendly?
• 2:59 Interesting that creating a relationship takes a few seconds and some crunching to do. I wonder what’s going on here exactly? Cube reprocessing?
• 3:43 Show Values As menu option – ok, this is what you get in Excel anyway, but am I right in thinking there are a lot more options here now than are available in 2007? Maybe I’m wrong, but this all seems to be Excel calculations rather than calculations happening in Analysis Services.
• 8:15 The Excel workbook containing this data is 203MB – interesting, because although Gemini is in-memory, it’s clearly possible to persist the data to disk if it’s being stored inside the workbook somehow.

One last point prompted by all the relational database-related terms we’ve seen: if I was a pure SQL Server relational database guy, with no interest in Analysis Services, I’d still like to get my hands on Gemini and use it server side if it’s this quick. Which goes back to a point I’ve made before in the past that if Analysis Services could be used inside SQL Server as an invisible layer to speed up the execution of data warehouse/BI style TSQL queries, in the same way as Oracle OLAP can be, it would be very cool. Just think of that working with Madison, in fact…