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Month: September 2009

A sweet solution for cherry picking

Don’t say “cherry picking” to people at information-intensive businesses like banks, airlines, and telecommunications companies. You can spoil their lunch if a big customer has just run off to a competitor.

Mark Albala says he has a tool that will warn of such a move. He’s president of InfoSight Partners, and he’s about to offer a new Twitter and blog sniffer to companies in the upper-midmarket and bigger.

Customers often precede their moves with questions about the competitor. Asking “what do you know about …?” on Twitter could be the first and last hint. Albala’s tool monitors such chatter on social media, industry blogs, and other external sources to know when something’s up.

“Your surprises aren’t all coming from your own data,” he says, “but from outside your organization.”

This thing will push notifications to iPhones and Blackberries. It won’t be expensive, he says. He expects the beta to launch in November.

Sustainability and BI: gone from drizzle to “storm”

Last fall’s Oracle OpenWorld had such a strong sustainability theme that I thought for sure I’d find products down in the exhibit hall. Not one. When I asked around, one guy even said sustainability management with BI tech “couldn’t be done.” (Read my TDWI story from back then.)

Now we see Terri Rylander’s post — she sees a “storm” brewing over this — getting six tweets. She deserves every one of them for extracting news from one muddy press release.

Migrating mindsets is the real challenge in ETL

I was intrigued by Donald Farmer’s recent tweet about ETL: “Migrating technologies is just work. Migrating people and mindsets is the real challenge.” I asked him to elaborate.

Donald is principal program manager of SQL Server Analysis Services at Microsoft. He sees “numerous” examples of migrating users who reject perfectly good methods in favor of “the Informatica way of doing it,” or the Datastage, or whatever they’re used to. Many IT workers see their career paths as not “DBA” but “Oracle DBA” or other brand, causing much extra expense in licensing and support. He writes in email, “CTOs have to battle that very hard.”

He sees this within Microsoft’s marketing analytics program. There, most recruits come from SAS — and they’re used to a much different approach.

SAS users, especially advanced users, are used to deploying a battery of statistical analysis and building a few carefully crafted models to deliver theoretically compelling results. In SQL Server, our users tend to iterate quickly and efficiently through many models, validating and testing as they go. These approaches and mindsets are very different.

We can generally answer the business questions that SAS answers, just as effectively for practical use — but SAS users will prefer the SAS methodology, and will often insist on it.

What’s a CTO to do? “The most effective technique I heard of for changing that mindset,” he writes, “was from an excellent CTO who simply made the SAS team responsible for their own budget. Two years later … well, SPSS not SQL Server, but the moral is sound.”

Visual analysis is pragmatic, not just “pretty”

So many of us who feel drawn to visual analysis can’t understand why everyone can’t see the value. “Pretty pictures,” the skeptics mutter. On Eager Eyes, Robert Kosara makes important points that I haven’t seen before.

Toward the end of his post he writes, “We need a new term.” He rejects the aged and indefinite “visualization” and the baggage-laden “visual analytics.” He prefers “visual analysis.”

Whatever we call it, it’s harder to use than it seems.

You have seen the bar and pie charts, but do you actually know what they mean? Do you know how to use them to tease the relevant information out of your data? Can you handle more than two dimensions of data and still find meaningful structures? There is so much more to visual analysis than what Excel offers you.

Good, but then he’s not clear. He writes, “The key problem is that people are much more interested in clicking through interesting pictures than learning about actual analysis work done using visualization.”

Which people? He can’t mean the ones who actually analyze. He must mean the casual users, the data consumers, the armchair analysts — and they will always click through. He writes that those who value visual analysis have to fight the idea that it’s just pretty “or risk the trivialization and marginalization of visualization as an analytic tool.”

You’d think the tide was coming in an threatening a sand castle. But from everything I’ve seen, genuine visual analysis seems to be more and more popular. Even elementary visual analysis works better than the ugly alternatives.

Who are we fighting? The ones who don’t care and never will? No, they’re no more a threat than fast food is a threat to good food. To most people, fast food is good enough — and so are pie charts.

The ones to watch out for are those who sell fast food under the good food banner — the ones who’d propagate sloppy techniques and call it visual analysis. That’ll really spoil our appetite.

For more on “good food,” don’t miss the “Information Visualization Manifesto.”