Q: With all of this change coming, can we finally call 2017 the year that traditional BI will be surpassed by modern BI?
A: Modern BI will become the new reference architecture. Data discovery has graduated to modern BI, and has become the norm for many organizations. Archaic reporting-first platforms are no longer complimentary and are increasingly being replaced. As a result, self-service will no longer be just for business analysts, it will scale more broadly. The death of legacy platforms will open up for more self-service. All employees in the organization will need to consume and have rich discovery from their data. If more people are enabled with great self-service technology, it will facilitate data literacy. This will also put bigger requirements on scale, performance, governance, security, etc. Self-service visualization vendors that can’t scale, and don’t have powerful engines behind them, won’t be able to keep up.
Q: Speaking of visualization, what growth do you see coming in that area in 2017?
A: Ideally, self-service visualization will become a commodity, accessible for all and freemium will be the new normal. If more people can “get on the bike”, it will bring many more people onto a personal analytics journey, increasing data literacy and ultimately information activism.
In 2017, the concept of visualization will move from “only visual analysis” to include the whole supply chain of data. This will mean that we’ll see visualizations also in unified hubs that take a visual approach to asset management, catalogues and portals, as well as visual self-service data preparation, underpinning the actual visual analysis. Further, more progress will be made in having visualization become a means of also communicating our findings. The net effect of this is that more people can do more with more in the data supply chain.
Q: Finally, the scope of advanced analytics has changed quite a bit over the past few years, where do you see it headed next?
A: Advanced analytics will continue to proliferate, but it’s dependent on experts, and should continue to be dependent of experts. It’s not a good idea to give a formula one car to someone that has just learned how to drive, therefore the algorithms (and not just the data) should be curated, and governed by the experts. However, many more should be able to benefit from those models once they are created, meaning that they can be brought into self-service tools.
There will also be an increased emphasis on custom analytic apps and analytics in the app. Everyone won’t, and can’t be both a producer and a consumer of apps. They should also have the ability to have rich explorations in data. Hence, the significance of meeting people where they are, with more contextualized and customized analytic applications, as well as analytics that reach us in our “moments”, will increase significantly. As such, open, extensible tools that can be customized by application and web developers will make further headway.
We want to thank Dan Sommer for his insights, make sure you are able to catch his upcoming webinar on January 11 at 1pm ET.