But is concern about data quality misplaced? There are at least two competing theories about this: what I’ll call the old school view and the big data movement. The old school view is that data quality matters: garbage in, garbage out. Thus, time is spent on data cleansing, extracting, transforming and so forth, and the strong belief is that this is time well-spent.
The big data movement has spawned a different worldview on data quality: the bigger, the better. The central idea here is that data-crunching in itself is cleansing. Things that don’t fit into the data model are like flotsam and jetsam — an insignificant, superficial layer on your deep ocean of insight.
In the real world, I’m finding that CIOs understand the big data quality perspective — and some would like to embrace it — but the old school wins out. And that’s not because these CIOs are risk-averse. Case in point is Greg Taffet, CIO at U.S. Gas & Electric, a Miami-based reseller of gas and electricity. The fast-growing company has doubled in size in every one of the last four years that Taffet has been there. Not that he’s complaining. He’s one of those CIOs who like to be where the action is. “I was previously the CIO and employee No. 4 at MXenergy, and left when it hit $1 billion in revenue. I was recruited here to do the same,” he said.
But the ever-changing business fundamentals make building “a real BI environment,” as he puts it, particularly challenging. When it comes to data quality, Taffet is definitely old-school: “The tools are really not that distinguishable. We have to know our business. We have to get into the minds of the executives and the operational people, so we can set up the tools to do their job.” For him, data quality is the bedrock of a real BI environment.
So, amid a whirlwind of growth, Taffet and his BI team meet weekly with people from finance, operations and sales to make sure there’s no disagreement about the quality of the data IT is collecting. “When we see something that is not expected, we drill down into the details and see if it is a variation on something that was not accounted for but should be, or something that should be taken out,” he said. It’s time well spent, he says, toward building that real BI environment.
But then Taffet’s not dealing with the volumes of data that qualify as big data — yet. “I still see that we have several years before we get hit with what we call big data,” he said. And until the tsunami hits, he’s sticking with old school. You?]]>
This was clear in a story I did this week on a snazzy hotel app deployed by the SLS Hotel at Beverly Hills. The free mobile app basically delivers round-the-clock service — a bottle of Dom Perignon, more shampoo — at the touch of an icon. IT Manager Eric Chao, the hotel’s point man on the mobile app, was happy to talk up the app’s front-end value: how it takes customer service to a new level, etc. But ask about the sophisticated analytics whirring on the backend that allow the hotel to figure out what a guest wants before he even knows it – and this reporter got the cold shoulder. The hotel PR squad flat out said no way.
“The app collects a lot of data,” was about all Chao could say. That, and it’s been “great for business.” Indeed. I have no doubt that the data collected contains information so valuable to the hotel that it’s not sharing it with anybody, never mind reporters.
Chao was not the only circumspect CIO I talked to this week. A CIO in the automotive industry I interviewed yesterday for an upcoming story on mobile BI stopped short when the topic of analytics came up. Routine analytics were handled in-house, he said, but the sophisticated stuff done by statisticians and data scientists—the secret sauce, the golden goose — that analytics was being outsourced. To whom? He couldn’t say, in fact, was prohibited from divulging that information to anyone outside the company.
My take on the silent treatment? If CIOs are not putting a lot of resources into advanced business analytics, they’re in trouble.
By the way, the same silence principle holds true for security too—in particular, app security, but shhhh that’s a post for another day.]]>
It certainly makes sense. Back in the waning days of 2011, CIO Executive Board Executive Director Shvetank Shah told us that BI projects were going to be where IT leaders focused their time, attention and money in 2012. In fact, he noted that this is what we’ll be looking at for the next two or three years. The focus on BI is part of a “megatrend” of projects shifting away from big ERP to big information.
A brief about Gartner’s study suggests this shift seems to be playing out right now. But what role will the cloud play? According to the consultancy, nearly one-third of 1,364 IT manager and business users surveyed in Q4 2011 already use or plan to use cloud-based BI tools to augment their BI functions within the next 12 months. A total of 17% said they have replaced or plan to replace parts of their core BI functions with a SaaS offering. What’s behind this? The key drivers Gartner cites are time to value, cost concerns and lack of available expertise.
So, as for the aforementioned assignment: I’ll be digging a little deeper, talking to folks who’ve already taken their BI to the cloud and if or when experts suggest you should too. One user of cloud-based business intelligence tools I spoke with today can’t imagine his company without them. Very pleased with what he and his end users are able to accomplish, he hooked me into an impromptu online demonstration. It certainly looks to be an exceptional tool for this food distribution company that does $3.5 billion in sales. But is cloud based BI right — and ready — to take the enterprise by storm? I’ll bring you some answers on SearchCIO.com next week.]]>