I love trick-or-treaters. As soon as dusk hits, our neighborhood gets swarms of cute little kids in adorable costumes, delighting us with their smiles as we drop a few pieces of candy into their pumpkin-shaped pails. As the night goes on, however, the kids get older,
more demanding and less creative with their costumes – you get the teenagers wearing pajamas asking for an extra handful and then (sometime around 10PM or later) you get very tall “kids” in street clothes wearing Friday the 13th masks banging on your door, demanding your king-size Snickers bars.
Do I tell them that they may have outgrown the trick-or-treating stage? Nah. I toss a few candy bars through the door and hope they’ll move along. Someone will eventually tell them. It just won’t be me.
Are you dressing up your analytics tool for non-analytics tasks?
In my last two posts in this platform migration series, I talked about how change can be a scary thing and how the process involved can seem just as frightening. But trust me, some of the technology challenges we faced during our own migration were also pretty disturbing.
Much like those king-size “kids,” at Dell we discovered that we had outgrown a well-known legacy analytics platform. We had also just acquired our advanced solution, Statistica – an easier-to-use analytics platform – and needed to be able to tell prospects that we use the product we are promoting. So we embarked on a great migration from a very expensive and dated analytics platform to Statistica.
During the migration, our team found that a number of analytics users at Dell were using the old product to manage and manipulate data before analyzing it. Sure, it could do the job but it was a really expensive way to move data around. And with all of the legacy code that was required to push data, it was unwieldy and unmanageable.
Unlike those grown-up trick-or-treaters, we quickly got out of denial and decided to do something about it.
How using the wrong tool for the job can haunt you
Using the wrong tool for the job may not sound like a big deal, especially if it gets the job done all the same. But in our case, it wasn’t just about using a tool with extraordinary analytics capabilities for ordinary jobs — it was also costing us licenses that didn’t need to be tied up on data management and data manipulation tasks. We couldn’t really blame our users for doing what they were likely taught by other Dell users at the time. But, it was an extremely expensive way to perform relatively common functions. And as an enterprise software company, we should know better.
So how did we overcome our fear of the unknown and commit to something that kind of scared us? We had to separate analytics from data management at the software level and at the organizational level. We moved data management and manipulation to our Toad Data Point solution, and analytics and modeling to Statistica. With each team empowered with the right tools, we now have data integration experts focused on data management and analytics experts focused on analytics. Sure, there were some awkward moments during the transition. But once you figure out what really works for you, life is simply easier â€• a lesson those teenage trick-or-treaters will learn soon enough.
New e-book: The Great Analytics Migration
If you’re using an expensive analytics software product dressed up in a data preparation costume or you’re facing a migration project of your own, read our e-book Statistica: The Great Analytics Migration. You’ll discover more information on how we successfully moved hundreds of users to a new platform in a matter of months, provided everyone with the right tools for the job and saved a ton in licensing fees. Follow our lead, and you can do it, too.