Editor's note: Allen Bonde, of embedded analytics leader Actuate (now a subsidiary of OpenText), believes that the opportunities around Big Data, Internet of Things (IoT) and wearables are about to change our world – and that of business applications. - bg
There are officially now more mobile devices in the world than people – the number crossed over in 2014 somewhere around 7.19 billion mark. Our craving to be connected 24/7 wherever we are means that mobile devices are multiplying around five times faster than we are. Our wired up lives and new creations in the area of wearables and sensors has triggered a data gold rush. But such growth does not come without its demands.
For a start, how are we going to manage the data swirling around us as the number of devices recording and transmitting information grows from smartphones, smart cars and intelligent fridges and home surveillance to industrial sensors. And how do we make sense of it? This data is only as valuable as the insight we can glean from it, which means it needs to be easily accessible (ideally visually), understandable, and ultimately actionable. What is required is smarter apps and devices – and smarter infrastructure that allows us to govern our information and deliver data-driven experiences that enable us to have more productive and relevant relationships in and out of the workplace.
It is important to note that we aren’t just talking mobile devices here, we are talking connected devices. Market research firm IDC estimates that there will be 30 billion connected devices by 2020, ranging from smartphones and desktops to industrial assembly lines and health diagnostic equipment.
At the same time, consumer wearables and other mobile devices have a dual role in this scenario as they not only create data, but they also consume (and display) it. With a deluge of new fitness, well-being and smart watches set to launch into the lower end of the market a whole new breed of data consumers are about to go live, producing even more data, and driving more demand for simpler, more personalized apps and experiences AND more robust back-end systems to help serve them up.
Look beyond the IoT buzz
However, while IoT is super exciting for sure, most (useful) enterprise information is still generated via people in old-fashioned transactional systems, Web interactions, social media and other channels. Harnessing our existing enterprise information stores and mapping critical information flows remains essential even before we tackle the so called “expanded Internet.”
The big issue, however, is that most enterprises have yet to articulate or establish a wide-scale Enterprise Information Management or “EIM” strategy or look at how newly connected people, devices, information and places (the new “inter-nets”) will transform their business landscape and relationships. But this doesn’t mean that businesses have to get all their devices online and monitor them before passing go. A good approach is to “think globally (with EIM) but act locally.” To look at what data and content sources are most critical to your top information flows. To find the best route to modernize existing apps with embedded intelligence. And to consider how you are handling and securing your most critical information. Then map out touch points where new, data-driven experiences and smart(er) apps can be a game changer. But through these efforts, still keep one eye on the emerging “Internet of Everything” and innovation around smart machines.
In fact, it looks like the “smart machine” era will be a major disruption later this decade and could be one of the most disruptive in the history of technology. Smart machines can deal with high levels of complexity and uncertainty and come up with their own theorems from the information they consume. Sure this is an “AI” type scenario, but like earlier generations of AI and machine learning, it is sometimes surprising how quickly these approaches leap from the lab into real life applications, especially when there is clear value for everyday tasks and users.
How will these next generation apps make individual users even more productive and successful? They will interact in more natural, more human ways, and they will truly “know you,” your likes/preference, and what information you want to share with merchants or even your employer. They will automate mundane activities, be true personal assistants, and be proactive rather than reactive when it comes to recommendations or insights. The possible result: an era where consumer IT, as opposed to enterprise IT, emerges as the real hub for innovation (See Gartner).
A word on small data and embedded analytics
Building on this theme, I’ve often said that computers like data, but people like answers. Data as we know is everywhere and growing by leaps and bounds. And as discussed, more data consumers are coming online every day. But this ubiquity (of users and devices, and user-generated content and data sources) actually drives the need for less complexity and simpler approach to deliver and visualize and operationalize data and its insights. This is the “last mile” after the sensors and sources have been wired to information flows and visuals; where value is created, and impressions are formed by your consumer and business users who see just the answers or insights or alerts that are most relevant to their task at hand.
For these reasons, the Small Data “movement” has established itself over the past couple of years as both a counterpoint to Big Data and a design philosophy. Driven by the goal of creating simpler, smarter, more responsive and more social apps, small data has become the darling of a growing number of designers and digital marketer alike. And with the growing need to reach mobile users and embed simpler, easier to consume experiences (on smaller screens), small data is even more relevant in the era of IoT and smart machines. I’d even argue that small data will be the “OS” for many of them!
So the pursuit of tools and approaches that turn information into actionable intelligence at any level has become key. But embedding (visual) intelligence in both traditional and emerging apps/devices means that designers need to overcome 3 interrelated challenges: Firstly we need to have easy access to big and small data via our design tools. Being data driven starts by connecting to all relevant enterprise and application data and content sources, including RDBMS, NoSQL, Hadoop, social media, and ultimately machine data.
Secondly, data management and visualization needs to be simplified. Good information design is a foundation, as is an ability to apply third-party visualizations, incorporate unstructured content, and create smart apps that will work in any environment including IoS or Android.
Finally, personalized delivery must be streamlined. For “best in breed” brands that serve millions of users, producing a white label, intuitive experience that requires little or no training is a must. Indeed, as a great Italian artist once remarked, “Simplicity is the ultimate sophistication.”
Embedded BI and analytics platforms available today provide a route forward for developing and embedding (high-scale) interactive visualizations – created from any source, packaged to meet modern development standards, and delivered via the right integration APIs to practically any device.
Whether these devices are part of the IoT (or Internet of Everything), or just today’s business infrastructure, technology planners need to look beyond the buzz words and seriously analyze the best ways to both create an overarching strategy for their enterprise information, and how to turn the most relevant data into useful, actionable intelligence that serves both customers and the employees that serve them.
Allen Bonde is vice president of product marketing & innovation at embedded analytics leader Actuate (now part of OpenText) – the company behind BIRT iHub™, BIRT Analytics™ and the Actuate Customer Communications Suite (for CCM)
Follow Allen on Twitter at @abonde or email him at firstname.lastname@example.org