BI Mashups

Tuesday I attended an interesting session presented by J.R. Arredondo and Dave Pae about putting together Enterprise Mashups using SharePoint Designer for WSS or SharePoint 2007. 

Mashups are one of those buzzwords, not unlike Twitter, FaceBook, etc., that sounds like a cool technology my 13-year old would be interested in but which I always try to approach with a bit of skepticism given my focus on business solutions that have ROI requirements.

And so it has been with "mashups" for me...on the radar but a bit unproven in terms of business value.

I think that needle has moved for me as a result of this session.  Of course, my primary focus is whether each new technique or technology is relevant to real-world BI solutions (not just something entertaining during a demo).

So how do I see mashups extending a traditional data-driven BI solutions?  Well, the ideal would be to take (A) traditional, planned data in a database or cube; (B) add in unstructured data (like sharepoint lists), and (C) access information on the web or from LOB systems using web services.

Modern BI solutions like PerformancePoint solve A+B, but C is not usually in the realm of end-users or analysts who assemble BI solutions.

While the Arredondo & Pae session didn't address a BI environment directly, I can see quite well how to adapt their techniques to do some interesting things. Using PerformancePoint we already have the ability to link to non-BI components, and by combining this with SharePoint designer mashup capabilities I can easily see integrating maps, internal web services and public services via various protocols.

If you haven't looked at Microsoft's Mashup page, take a look at it here: Enterprise Mashups.  And if you're not aware that SharePoint designer is now free, download it here and take a look at ways to design rich mashup pages in sharepoint.

Today I had the pleasure to attend Donald Farmer and Kamal Hathi's session on the Gemini project.  I've seen several of Mr. Farmer's presentations on BI and Data Mining, and I'm never disappointed at his skills and depth of knowledge!

Gemini is an in-memory, Excel-based, analysis services orientated technology that brings the power of dimensional modeling to a primarily Excel skilled audience--with the promise that the output of Gemini can be forward-engineered into managed Analysis Services solutions. 

Donald's quite entertaining slide deck was a major departure from the typical corporate spin that we're accustomed to seeing (and that I'm personally accustomed to producing) when we educate potential technology users.   

The slide deck casts the analyst, boss and IT admin as silent movie characters, where the analyst and IT professional struggle to keep the boss happy within the limitations of their skills and the existing content in the corporate DW.  It's the all-too-familiar "I need that analysis by tomorrow" versus "it takes time to put that data together".  Terribly apt and consistent with what we see in the "BI trenches" every day.

The silent movie theme stresses that this situation hasn't changed that much in many decades (and in any event in the two decades I've been working on BI solutions).  Of course, the slides were endlessly entertaining while driving home these points!

As for the "Gemini" product, it's quite exciting.  BlueGranite has been in the business of helping our clients' analysts pull info together quickly and make it meaningful since the ProClarity days.  One of my lingering concerns has been that--since ProClarity was acquired and the future of its core technology became uncertain--what tools within the Microsoft product suite would serve these "data diggers"? 

Excel pivot tables against SSAS cubes are fantastic--but how to make sure analysts can get data pulled together by the cube designer fast enough to meet business needs?  If the corporate governed DW/Cubes evolve slowly, how can analysts fill in the gaps? 

Today I still recommend ProClarity for the deep data analysts (as a complement to Excel), as it still provides more flexibility and richer visualization than Excel pivot tables for advanced analysts.  But I think Gemini may one day (hopefully soon) deliver even more, and really become the data digger's tool of choice.

Gemini is clearly intended to fill the analyst gap.  And in so many ways I think it will. It's at once a more approachable way for non-OLAP users to build rich dimensional models, a way to make more dynamic data integrations using the familiar Excel environment, and a rich OLAP query tool to be used against these analyst-generated models.

In truth, I can easily see even seasoned SSAS pros (including myself) using Gemini during prototype and early development, in addition its intended less sophisticated audience.

The things I love about Gemini:

1. Users import data from all types of sources:
   a. Structured relational
   b. Existing OLAP Cubes
   c. Subscribe to "Service Documents" (a form of RSS feed that contains tabular data)
   d. Paste in any tabular data (e.g. copied to clipboard from a web page)

2. Fast processing of large data volumes (100M rows demonstrated, 20M demo'd on a netbook)

3.  Ability to add calculated measures at the Excel pivot-table layer (sweet!)

4.  Ability to connect to Gemini models as SSAS data sources (rocks!)

5.  Tight integration with SharePoint as a basic architectural construct

6.  Translation of most OLAP concepts to Excel terminology more familiar to analysts

Some things I would like to see improved, or clarified. 

I would have asked these questions, but Q&A was cut short today due to time constraints...

1. As simple as they seem to MDX people (like me), my sense is the DAX expressions are going to be too complex for many of the analysts I train.  It reminds me of PPS-P PEL, in that the expressions are intended to be simplified from MDX, but they're still complex and require multidimensional thinking--which isn't a gift many of us are born with.   PEL generated lots of push-back from analysts when I demonstrated it to "real customers", and I fear DAX may as well.

2. To address #1, I hope the product team will consider following the model ProClarity set with it's KPI Designer, which allows users to use wizards to build calculated measures such as ranking and bubble-up exceptions.  KPI designer users build complex MDX without knowing that's what they're doing.  I still train new users on these tools, and it's a positive for them to use wizards (rather than purely language constructs, as with DAX).

3. I'd like to see some MDM tie-in to ensure that already accepted calculations, data sources, etc., can be drawn upon and re-used in a Gemini solution.  I can see a BI governance issue (and IT objection!) if many analysts are building silo BI solutions without some centralized baseline to start from.  Gemini doesn't prohibit a DW/MDM baseline, but it doesn't appear to promote one either.

4. Security really wasn't addressed in the session.  If analysts will be pulling 100M rows of fact data into a desktop solution…how does a corporate IT policy ensure that that such huge volumes of data isn't lost in the back of a taxi?  BitLocker would be a convenient answer to this question, but I hope it isn't the only one.

5. Data mining--not sure if it's possible to incorporate DM models into the Gemini models, but the combination of capabilities on the desktop would be really fantastic!

In-memory OLAP is a hot technology, and as illustrated by Donald's slides, the world has been waiting far too long to put such powerful tools in the hands of typical analysts.  I can't wait to see how this possibly disruptive technology impacts the wide swath of users its intended to benefit!