What’s Next for Data Analysis? Part I

I’m commonly asked this question in a variety of circles and on several continents. I consider it one of the more interesting aspects of my job to have these types of predictive, future-oriented conversations with a wide variety of people: customers, partners, technologists, journalists, analysts, consultants, entrepreneurs, financial analysts, researchers, and so on. So, I sat down recently to simply document my answer to the question “What’s Next for Data Analysis?” Here are my thoughts.

I believe the next few years will be an amplified continuation of what we've seen in the past few years, albeit with a severely web-focused, any-client device emphasis. Many of the patterns I’ll cite have been underway for some time; it’s just that the more simple and affordable ability to implement them has only recently caught up with the ambition.

Here goes. Next-generation data analysis will . . .

. . . embrace the rise and use of “big data” for nearly any size organization. I’ve long said that big, distributed data is not limited to big enterprise and many companies will find valuable insight because they can sift through it all to find new answers.

. . . require a more varied set of "analytics" - from responsive and unstructured to predictive and highly-structured. There are many ways to use data productively. Sometimes understanding the past is the most important point. Sometimes being able to predict the future, based on the patterns of the past, is required. The lines here will blur and more organizations will need both and many types in between.

. . . demand greater use of low latency analysis, which decreases the time between a business event occurring, its analysis, and a decision that is based on it. Sometimes this is referred to as “real-time BI” and other times “streaming analytics”. Let’s just call it useful and necessary in more environments each year.

. . . be untethered from traditional client computing network practices. I’ll repeatedly say “analytics anywhere”, which means purely web-based, open standards-aware, (multi-) thin client architecture. That’s a mouthful, but it needs to be the starting point for business intelligence system design (and this is where the mega-vendors’ mostly aged architectures fall short, btw). The most appropriate analytic experience should be deliverable to any device, because both the thin client or native mobile front-end application (where necessary) and the back-end (web) services understand and adapt. More users will expect this every year.

The combination of these clear patterns and trends is surely driving our product and technology roadmap at Jaspersoft. It’s also positively impacting our work with our far-flung community, where so many of our ideas become grounded. Internally, we talk about speeding the movement of “data to dashboard” so the user has the advantage of working with timely and relevant data, presented elegantly and in the proper context. This is our central thought. If you’re interested in learning more about the analytics landscape, from Jaspersoft’s perspective, we’ve published this white paper.

Next post, I’ll describe the recent BI and data management technologies that stand the most to gain as these shifts occur. In the meantime, let me know what you think.

Brian Gentile
Chief Executive Officer
Jaspersoft