Alyssa Blackburn in conversation with Tech means Business podcast host, Joe Green. Source: Tech Wire Asia

Business Intelligence thought leaders: Alyssa Blackburn of AvePoint

Back in the 1980s, the term business intelligence came with notions of management consultancy, where expensive professionals would swoop into a workplace with insights on which improvements could be based. But in the age of data, BI is no longer the purview of those shoulder pad-wearing, Porsche-driving executives. The information at all business’s fingertips makes business intelligence highly accessible – it’s “simply” a case of mining the insights. But therein lies a long list of challenges. Instead of business intelligence, perhaps we should be talking about business analytics (as in, data analytics).

Platforms that help organizations turn their data resources into business gold are latter-day alchemists, and the success of BI platforms is analogous, largely, to the effectiveness with which they ingest, process, and present data. Some solutions specialize in ingestion, or presentation of information, to take two examples. Others offer the full gamut of operations in the data/BI arena, while some are establishing new paradigms like data abstraction layers that might be regarded as a natural evolution from data lakes that duplicate discrete silos’ contents.

At Tech Wire Asia, and its sister site, Tech HQ, we’re gathering thought leadership from this dynamic market space of business analytics, a scene that changes as quickly as the nature and breadth of available information changes. Alyssa Blackburn, Director of Information Management at AvePoint spoke to us recently about how the concept of business intelligence has changed over the last few years and how there are new challenges for data professionals, even as older issues (such as incomplete or unavailable data sets) may be receding.

“[All of us] have really made an effort to change the way that we approach data, how we create our data, how we store our data […] sometimes more successfully than others. But even more than that, what I would say is that we’ve also figured out that we have this new, incredible repository of stuff, which is electronic content, be it data, be it information. […] And there’s opportunity there, to monetize that, not, ‘I can sell this,’ but for other purposes; monetize it for my own internal benefit, […] for better insights, better analysis. And I think that organizations are really starting to take that seriously.”

Business intelligence to business analytics

Many organizations are well aware that they have data resources accrued for the last few years – at least, for as long as there’s been a digital element to the business. But receiving value from the resource is the challenge, beginning with realizing where data might be hiding away. Alyssa explained. “How do we actually find the stuff that’s valuable? Just hold on to that, and then be able to do something really sensible and wonderful and transformational, versus, ‘I’ve just mined all of this stuff up from the ground,, […] but I can’t do anything with it, because I don’t know what’s actually good.'”

When overwhelmed with possibilities (think about whole hours spent just choosing what to watch on Netflix as an example of the effects of too much choice), sometimes the key decision is what to throw away (“in an appropriate and defensible way,” Alyssa added). But what happens then is up to the individual company? In some cases, the questions being asked may be wrong or, at least, misdirected.

“The most important thing is to understand what you want the outcome to be. [An organization] might come and say to me, ‘I really need this button to be blue. The button’s got to be blue!’ […] But what do you actually need at the end? And they might say, ‘I need particular reporting of how many things were created over a particular period of time.’ Well, it doesn’t really matter if the button’s blue or red then does it, if it does the same thing?”

Once the desired outcomes are defined, business analytics becomes a target that’s easily focused on, and the clever use of platforms like AvePoint comes into play. “Technology should be there to make things easier, to make things more efficient, but it shouldn’t necessarily drive the process.”

For the pages of a website primarily focused on technology, it’s an approach that’s much more heavily weighted on the side of the business rather than the technologists’ fascination with how data is assayed, parsed, sanitized, run through models, and answers presented. AvePoint’s platform does all those things, but it’s not those things that necessarily create her unbounded enthusiasm for the possibilities. For Alyssa, the tech does the heavy lifting and does it well:

“We should get the technology to do that, and that’s amazing. But if we don’t know what [the outcome should be], none of the technology is ever going to be any good. I’ve got great software! But if you don’t know what you want it to do, it’s never quite going to meet those needs.”

Keep coming back to the Data & BI Spotlight area on this site to get more Thought Leaders’ insights and opinions.