By Scott Robinson
Microsoft has drifted into the habit of bundling its most impressive new
capabilities as peripheral trinkets. But in the case of SharePoint 2013,
they’ve set a new record for understatement. Yes, SharePoint 2013
is feature-rich almost to a fault, and yes, most of the new stuff is
big-banner game-changing (Social computing! SharePoint-in-the-cloud!).
But some of the most powerful items are geeky little widgets
that barely get a mention on TechNet, and when it comes to SharePoint
2013, the In-Memory BI Engine tops the list.
Out-of-the-box Excel vs. Pricey business intelligence
Office SharePoint Server (MOSS), Microsoft has faced a huge quandary: how
to get more business-side users to exploit the rich business intelligence
(BI) tools in SQL Server? Excel turns out to be the weapon of choice, since
everybody and their great aunt know how to use it. As analytics have begun to
supplant strategic imperative on the front lines of competition, this became an
even stronger priority (in SP 2010), making Excel an indispensable component in
the Microsoft BI toolkit. If I can play out ad hoc analytics via Excel, without
the inconvenient, expense, and limited scope of a third-party or home-grown BI
app, why in the world wouldn’t I?
There are some good reasons, if you listen to the
third-party app marketers. Excel is a disastrous BI client, they maintain,
because it provides no means of detecting an error in the set-up of an
analytical job; its ubiquity is a red herring, because it invites people into
the analytics business who don’t know squat about analytics; and it simply
isn’t designed to rally the processing resources that big data requires.
The first two are training issues, and not Microsoft’s
problem. But that last objection is a valid one, and has been no small hurdle
for getting in-memory analytics onto the SharePoint community’s radar, where it
certainly should be. And now that hurdle has been cleared.
Big data, big memory
The In-Memory BI Engine (Vertipaq, or xVelocity)
is an efficiency enhancement that optimizes memory for high-volume analytical
processing. Columnar storage, in-memory caching, compression and algorithms for
aggregating and scanning data in parallel are leveraged to empower the business
user to potentially process hundreds of millions of rows of data in an ad hoc
process (the implementation of OData and
the expansion of PowerPivot
now empower that same user to gather those hundreds of millions of rows from
many different sources, but that’s a different blog entry).
The under-the-hood efficiency means that this data crunch
happens in seconds, not minutes, and that is itself a game-changer for ad hoc
analytics. But an even greater resource barrier has been the fact that Excel
can’t hold that much data in one sitting, and SharePoint can only store 2GB,
However, that’s no longer an issue. Excel Services can now
make use of as much free memory as is physically available on the box, meaning
that the ceiling in terms of in-memory processing is now virtually limitless:
if you need more, just scale up. Therefore, the 2GB object size limit (which is
actually a SQL Server limit) is unlikely to be a problem, because you don’t
need to do temporary storage if you’ve got that much memory available, and
analytical results tend to be relatively small, compared to the body of data
that produces them.
Microsoft’s BI tools, then, are not only improved, but have
arrived squarely on the doorstep of serious analytics. These new toys don’t
help the learning curve, but they certainly place unprecedented processing
power in the hands of the business user. Just don’t tell the BI app marketing