Last week, Tableau hosted a session on the evolution of Business Intelligence in Portland that I had the chance to attend. Although I did review their Top 10 trends in BI when they released them earlier this year, the presentation and discussion ended up being pretty interesting. A few of the topics really resonated with me and I thought we could dig into them a bit more.
Modern BI becomes the new normal
The session (and report) kick off by highlighting Gartner’s Business Intelligence Magic Quadrant and the shift away from IT-centric BI over the last 10 years. Regardless of who’s discussing the trends (Gartner, Tableau or otherwise..) and if or when they come to fruition, it’s important to dig deeper. **Reports like those by Gartner are good guideposts for trends and technologies to exam; saw that mentioned somewhere recently, comment for credit.
That said, I think we can agree that the overall landscape of technology and the way that organizations of all sizes are taking advantage of it in the domain of business intelligence has improved over the last decade.
So does that mean modern BI has truly arrived?
Although some ideas come to mind when I hear the phrase..
What is modern business intelligence?
And do we all think of the same things when we discuss it….?
No not that…
So I spent 5 minutes on Google looking for answers:
Once you get past the sponsored ads, the first couple pages talk mostly about the types of platforms and tools out there, but not modern BI itself.
Tableau offered a white paper on a modern approach to BI ( I haven’t had a chance to read yet)
A post that came up from a couple years ago by TIBCO; it touted that “for BI to be useful in a modern architecture, it needs to be embedded inside the most popular applications.”
Subsequently, embedded analytics and data products are definitely a thing, but have since broken off from modern BI to become their own trend.
Wikipedia didn’t have the answer either...
So is modern business intelligence about the platform or tools more than the practice? To curb my Descartian dilemma, let’s agree that:
I’ll do us the favor of sidestepping the what is modern rabbit hole for the time being...
So for the purpose of our discussion, when we are talking about modern BI, we must be primarily referring to the technologies we use to support the better decision making. Jumping back to Gartner’s take on a modern BI platform, it’s:
A self-contained architecture (basically breaking functionality into independent systems….so sure..we have platforms and tools for all that....)
That enables nontechnical users to autonomously execute full-spectrum analytic workflows from data access, ingestion and preparation to interactive analysis, and the collaborative sharing of insights (That’s a lot of stuff to cover, for a non-technical user to execute on...so no, we aren’t quite there yet..)
Since we did agree at the outset that the technology options available for these types projects have improved significantly over the decade and we’ve also made some strides in how we use it the technology, we must be getting closer to modern BI Shangri-La. That being said, with the ever growing number of data sources, new platforms for all sorts of things (pretty much every company is a data company or trying to be) as well as the increasing number of places we need to get our data, it’s a complex landscape to navigate. Comparing that with our working definition, most efforts are still very much a cooperative effort between IT + data engineers and data analysts + business users to get where we are trying to go with BI.
In conclusion, although the current state of BI may be a bright contrast to the dark ages of yesteryear, companies are still struggling to realize nirvana of modern business intelligence (something akin to Bradley Cooper’s character in Limitless…)
There has to be an easier way...
If you are grappling with some data challenges of your own, we’d love to hear from you about the types of projects you’re working on. Keboola is helping data-driven organizations bridge the gap between the data and those data workers and business users that so desperately need it for “the collaborative sharing of insights.”
Please stay tuned as we continue to wrestle with other philosophical issues in data (and whether you’re safe from it,) business intelligence and the inevitable arrival of our AI overlords.