BIME Business Intelligence Predictions for 2015

Business intelligence in 2015 will see greater social media involvement, data mining applications, health data analysis, data-driven drones, and BI in the cloud.

By Rachel Delacour, CEO of BIME Analytics, Dec 2014.

Business Intelligence As cloud services become the ubiquitous, invisible fabric of our private and professional lives, business intelligence (BI) and analytics emerge as the crucial components to make sense of data large and small. According to Rachel Delacour, CEO and co-founder of BIME Analytics, easy-to-use data discovery tools are the equivalent of navigation and mapping services for the data-driven world.

From the rise of social BI and data-driven public health to analytics as the backbone of a drone ecosystem ready to take flight, here are Delacour’s five data predictions for 2015.

1. Intelligence will either be social - or nothing special.

Much like gamification was about a UI that effortlessly engages a user, future BI and analytics will be designed around real human beings. While the old model pushes or insights to users, the future belongs to live, bi-directional exploration of data -- similar to the give and take consumers love in social networks or personal apps. Pick data sets with a virtual circle of curious minds and visualize them collaboratively, bookmark a specific view and exchange live comments just like you would in a gamer or CRM landscape.

Social analytics also means service providers have to rethink their approach. Going forward, they have to help users right in the app or dashboard, offering live support 24/7. It gives them a 360-degree view of how people use analytics, where they excel and where they get stuck. This dynamic exchange will significantly shorten the time to push out enhancements and updates for all.

2. Data mining is the new black

Whether or not you understand the R programming language, Apache Mahout or concepts such as Holt-Winters multiplicative exponential smoothing: data mining will be sprinkled into a lot of modern applications in clever ways, hiding all the complexities but keeping the magic. It’s something we have become accustomed to when Amazon recommends books or the Akinator app can guess the character we have in mind. Access to those advanced algorithms will become an integral and common part of the analytic tool set available to the average user.

What’s more, applications will find clever ways to make use of such advanced data mining algorithms in everyday situations. For instance, the recent update to Gmail now parses emails and automatically adds events mentioned in messages to the calendar, thanks to natural language processing. So all you need to bring to ring in the new year is curiosity and a modern browser on a tablet.

3. Staying healthy means more data to catch and cure diseases

One of the many lessons of the Ebola outbreak is that the world need a far-flung and thorough early-warning system. Public health officials can't afford to be in the dark about new cases, existing patients and their extended networks, or promising candidate drugs for a cure.

Experts rightly lament that healthcare is “data rich” but “analysis poor,” and the consumer space demonstrate how to get out of this dilemma. Inexpensive trackers and apps for individuals lead the way for how to deal with health at large, from medical-grade apps to public health networks. We’ll witness the emergence of services and tools that accompany patients and doctors along their journey together, creating a data-driven connection much earlier than when traditional preventive systems usually kick in. Electronic health records are already being collected, but we’ll see progress in three specific areas: more compatibility between these different data stores, better integration with new analytics platforms specializing in health outcomes, and finally better integration between consumer-grade fitness apps and serious medical applications.

4. Drones need data to do good

Leaving aside the headline-grabbing stories about drones making deliveries and being shot down by upset neighbors, the rise of unmanned or autonomous devices on land or in the air depends on one key thing: a reliable, bi-directional data feed to parse. Drones in the civilian world will do a lot of good in 2015, but they need to gather loads of data and feed them into analytics platforms that help humans -- whether it’s about environmental sensing, surveying natural disasters and relief efforts, or making sense of traffic patterns and other urban phenomena. Connecting to a smart node to offload data for analysis and receive instructions on what to do next will be a crucial factor for the success or failure of these systems, for experts as well as the general public.

As robots and UAVs become almost as affordable as a good vacuum, more and more services will pop up to help manage the novel chores of the data-driven world. Big Data, in short, will help define and build out the world of tomorrow’s robots.

5. The cloud is everything, everything is in the cloud

Don’t expect the “race to zero” in the cloud economy to let up in 2015. Quite the contrary. Big vendors such as Amazon, Google, and Microsoft will keep tweaking their services while dropping prices, and that’s a good thing for companies moving more and more of their data and services into the cloud. In 2015, the cloud will be everything, and everything will be in the cloud. As the plumbing of our connected world becomes cheaper and almost invisible, businesses can use this abundance of resources to quickly add high-value services to run on top. Owning, running and maintaining a proprietary data center will soon be a thing of the past, except perhaps for the very largest companies or those with the most sensitive data.

The rest of the enterprise community will count their beans in 2015 and break into a big smile. While the big guys figure out how to make a profit off a booming business with low margins, organizations can start thinking about how to benefit from vast resources at rapidly shrinking prices. They will be more inclined to experiment with tools to crunch terabytes of data. Big data, in short, will come with an ever smaller price tag.