SAS charged its sales force with selling 2,000 licenses for Visual Analytics in 2013; the jury is still out on whether they met this target. There’s lots of marketing action lately from SAS about this product, so here’s an FAQ.
Update: SAS recently announced 1,400 sites licensed for Visual Analytics. In SAS lingo, a site corresponds roughly to one machine, but one license can include multiple sites; so the actual number of licenses sold in 2013 is less than 1,400. In April 2013 SAS executives claimed two hundred customers for the product. In contrast, Tableau reports that it added seven thousand customers in 2013 bringing its total customer count to 17,000.
What is SAS Visual Analytics?
Visual Analytics is an in-memory visualization and reporting tool.
What does Visual Analytics do?
SAS Visual Analytics creates reports and graphs that are visually compelling. You can view them on mobile devices.
VA is now in its fifth dot release. Why do they call it Release 6.3?
SAS Worldwide Marketing thinks that if they call it Release 6.3, you will think it’s a mature product. It’s one of the games software companies play.
Is Visual Analytics an in-memory database, like SAP HANA?
No. HANA is a standards-based in-memory database that runs on many different brands of hardware and supports a range of end-user tools. VA is a proprietary architecture available on a limited choice of hardware platforms. It cannot support anything other than the end-user applications SAS chooses to develop.
What does VA compete with?
SAS claims that Visual Analytics competes with Tableau, Qlikview and Spotfire. Internally, SAS leadership refers to the product as its “Tableau-killer” but as the reader can see from the update at the top of this page, Tableau is alive and well.
How well does it compare?
You will have to decide for yourself whether VA reports are prettier than those produced by Tableau, Qlikview or Spotfire. On paper, Tableau has more functionality.
VA runs in memory. Does that make it better than conventional BI?
All analytic applications perform computations in memory. Tableau runs in memory, and so does Base SAS. There’s nothing unique about that.
What makes VA different from conventional BI applications is that it loads the entire fact table into memory. By contrast, BI applications like Tableau query a back-end database to retrieve the necessary data, then perform computations on the result set.
Performance of a conventional BI application depends on how fast the back-end database can retrieve the data. With a high-performance database the performance is excellent, but in most cases it won’t be as fast as it would if the data were held in memory.
So VA is faster? Is there a downside?
There are two.
First, since conventional BI systems don’t need to load the entire fact table into memory, they can support usage with much larger datastores. The largest H-P Proliant box for VA maxes out at about 10 terabytes; the smallest Netezza appliance supports 30 terabytes, and scales to petabytes.
The other downside is cost; memory is still much more expensive than other forms of storage, and the machines that host VA are far more expensive than data warehouse appliances that can host far more data.
VA is for Big Data, right?
SAS and H-P appear to be having trouble selling VA in larger sizes, and are positioning a small version that can handle 75-100 Gigabytes of data. That’s tiny.
The public references SAS has announced for this product don’t seem particularly large. See below.
How does data get into VA?
VA can load data from a relational database or from a proprietary SASHDAT file. SAS cautions that loading data from a relational database is only a realistic option when VA is co-located in a Teradata Model 720 or Greenplum DCA appliance.
To use SASHDAT files, you must first create them using SAS.
Does VA work with unstructured data?
VA works with structured data, so unstructured data must be structured first, then loaded either to a co-located relational database or to SAS’ proprietary SASHDAT format.
Unlike products like Datameer or IBM Big Sheets, VA does not support “schema on read”, and it lacks built-in tools for parsing unstructured text.
But wait, SAS says VA works with Hadoop. What’s up with that?
A bit of Marketing slight-of-hand. VA can load SASHDAT files that are stored in the Hadoop File System (HDFS); but first, you have to process the data in SAS, then load it back into HDFS. In other words, you can’t visualize and write reports from the data that streams in from machine-generated sources — the kind of live BI that makes Hadoop really cool. You have to batch the data, parse it, structure it, then load it with SAS to VA’s staging area.
Can VA work with streaming data?
SAS sells tools that can capture streaming data and load it to a VA data source, but VA works with structured data at rest only.
With VA, can my users track events in real time?
Don’t bet on it. To be usable VA requires significant pre-processing before it is loaded into VA’s memory. Moreover, once it is loaded it can’t be updated; updating the data in VA requires a full truncate and reload. Thus, however fast VA is in responding to user requests, your users won’t be tracking clicks on their iPads in real time; they will be looking at yesterday’s data.
Does VA do predictive analytics?
Visual Analytics 6.1 can perform correlation, fit bivariate trend lines to plots and do simple forecasting. That’s no better than Tableau. Surprisingly, given the hype, Tableau actually supports more analysis functions.
While SAS claims that VA is better than SAP HANA because “HANA is just a database”, the reality is that SAP supports more analytics through its Predictive Analytics Library than SAS supports in VA.
Has anyone purchased VA?
A SAS executive claimed 200 customers in early 2013, a figure that should be taken with a grain of salt. If there are that many customers for this product, they are hiding.
There are five public references, all of them outside the US:
SAS has also recently announced selection (but not implementation) by
OfficeMax has also purchased the product, according to this SAS blog.
As of January 2014, the four customers who announced selection or purchase are not cited as reference customers.
What about implementation? This is an appliance, right?
Wrong. SAS’ considers an implementation that takes a month to be wildly successful. Implementation tasks include the same tasks you would see in any other BI project, such as data requirements, data modeling, ETL construction and so forth. All of the back end feeds must be built to put data into a format that VA can load.
Bottom line, does it make sense to buy SAS Visual Analytics?
Again, you will have to decide for yourself whether the SAS VA reports look better than Tableau or the many other options in this space. BI beauty shows are inherently subjective.
You should also demand that SAS prove its claims to performance in a competitive POC. Despite the theoretical advantage of an in-memory architecture, actual performance is influenced by many factors. Visitors to the recent Gartner BI Summit who witnessed a demo were unimpressed; one described it to me as “dog slow”. She didn’t mean that as a compliment.
The high cost of in-memory platforms mean that VA and its supporting hardware will be much more expensive for any given quantity of data than Tableau or equivalent products. Moreover, its proprietary architecture means you will be stuck with a BI silo in your organization unless you are willing to make SAS your exclusive BI provider. That makes this product very good for SAS; the question is whether it is good for you.
The early adopters for this product appear to be very SAS-centric organizations (with significant prior SAS investment). They also appear to be fairly small. If you have very little data, money to burn and are willing to experiment with a relatively new product, VA may be for you.