Returning from Inspire 2016 –the annual user conference from Alteryx – as I write this, I can’t get away from one burning question rattling around my brain: Why do people hate their data so much?
Before delving into that one, let’s provide a little background here.
Alteryx likes to distinguish itself as a “platform” –as opposed to a point solution – for self-service data analytics. Including capabilities for data blending (some have called it integration), data preparation, enrichment, and predictive/advanced analytics, the solution is geared primarily toward data scientists and business analysts, especially those that deftly balance a modicum of technical acumen with a healthy dose of business expertise.
Accordingly, the Inspire conference is chock full of folks whose primary job function involves extracting meaningful insight from data, a task monumentally easier said than done. Through casual conversations, and after listening to several “before and after” style customer accounts, a common thread that emerged was a deep dissatisfaction with the raw material used to create insight.
So, why do people hate their data? There are several reasons (in no particular order):
- It’s gross. Riddled with corrupted, duplicated, incorrect, or absent fields, the typical data source has major quality issues. To make matters worse, these issues arise regardless of data source, be it an application, an operational data store, a data warehouse, or just a spreadsheet.
- You need the Keymaster of Gozer just to find it. In the heat of analysis, with all the brain-burning and number-crunching, how often does someone need data that isn’t immediately at their fingertips? All. The. Bleeping. Time. For many of these poor souls, adding a field to a data set, or, God forbid, accessing a net-new data source, involves kneeling at the feet of IT and kissing the ring.
- It flows like molasses. IT isn’t always the sadistic gatekeeper that they’re often made out to be, but even when IT enjoys a healthy relationship with the business side, it can take days, weeks, or months to get the data needed to answer the mission-critical business questions at hand.
With these ideas in mind, I had to go back to my own research to find out if this was a fluke due to an obviously self-selecting audience or if this hatred is indeed as rampant as it appears.
Well, as it turns out, the hate is real. Across several key metrics, the average company is really not super-thrilled with their data. Fewer than 20% of typical organizations report being satisfied with things like data quality and expediency.
On the other hand, if you compare them to Best-in-Class companies (in this case measured against their data preparation capabilities), the research shows some light at the end of the tunnel (Figure 1).
Aberdeen’s most recent study on data preparation revealed some of the reasons these top companies were able to achieve a much higher degree of user satisfaction. In addition to the data management / data preparation technologies in use, these companies were also focused on increasing the accessibility of their data without compromising its security or integrity.
Ultimately, the Alteryx solution aims to address these issues and empower a wider variety of users with more agility in handling data and creating insight from the analysis of it. Over the course of a full day of activity for us analysts, Alteryx executives laid out their go-to-market messaging, product roadmap, and sales strategy.
Doubling down on capabilities for data preparation, governance and enterprise readiness, data connectivity, and advanced analytics, the features and functionality seem to be moving in the direction of IT, but with the ultimate goal of empowering more users on the business side of the house. As a seemingly curious juxtaposition, this balancing act – IT/enterprise readiness and credibility with a business-friendly interface – is core to the Alteryx strategy.
At the end of the day, however, Alteryx serves a very specific and fickle audience. Data scientists and business analysts are a growing community, due to the many analytics-driven educational tracks offered by today’s universities (a trend that Alteryx is betting on and contributing to), but they are still a relatively rare breed.
These people have jobs and careers that depend on their ability to find a needle of insight in a haystack of raw data. They have the right to be frustrated with their data. As the research proves time and time again though, technology can only get them part of the way there. In addition, they need executive-level support, an enhanced analytical culture, and an enabling IT department rather than a preventative one. In other words, they need all sorts of fuzzy, non-quantitative things that make a big difference.
So are solutions like the Alteryx platform the cure for data hate? Well, while it isn’t entirely up to them, it’s a start!