A key factor is that there's simply much more data in many forms to analyze than before. We're in the middle of an ongoing, accelerating data boom. According to Science Daily, 90 percent of the world's data was generated over the past two years. The fact is that with technologies such as Hadoop and NoSQL databases, we now have unprecedented access to cost-effective data storage. With vast amounts of data now storable and available for analysis, people need a way to sort the signal from the noise. People from a wider variety of roles—not all of them BI users or business analysts—are demanding better, greater access to data, regardless of where it comes from. Qlik Sense's fundamental design centers on bringing varied data together for exploration in an easy and powerful way.

At the same time, we are seeing a shift in how computation occurs and potentially, how information is managed. Fundamentals of the computing architectures that we've used for decades, the spinning disk and moving read head, are becoming outmoded. This means storing and accessing data has been around since Edison invented the cylinder phonograph in 1877. It's about time this changed. This technology has served us very well; it was elegant and reliable, but it has limitations. Speed limitations primarily.

Fundamentals that we take for granted today in BI, such as relational and multidimensional storage models, were built around these limitations. So were our IT skills, whether we realized it at the time. With the use of in-memory processing and 64-bit addressable memory spaces, these limitations are gone! This means a complete change in how we think about analysis. Processing data in memory means we can do analysis that was impractical or impossible before with the old approach. With in-memory computing, analysis that would've taken days before, now takes just seconds (or much less). However, why does it matter? Because it allows us to use the time more effectively; after all, time is the most finite resource of all. In-memory computing enables us to ask more questions, test more scenarios, do more experiments, debunk more hypotheses, explore more data, and run more simulations in the short window available to us. For IT, it means no longer trying to second-guess what users will do months or years in advance and trying to premodel it in order to achieve acceptable response times. People hate watching the hourglass spin.

Qlik Sense's predecessor QlikView^® was built on the exploitation of in-memory processing; Qlik Sense has it at its core too.

You may know that more than a billion people use Facebook, but did you know that the majority of those people do so from a mobile device? The growth in the number of devices connected to the Internet is absolutely astonishing. According to Cisco's Zettabyte Era report, Internet traffic from wireless devices will exceed traffic from wired devices in 2014.

If we were writing this chapter even as recently as a year ago, we'd probably be talking about mobile BI as a separate thing from desktop or laptop delivered analytics. The fact of the matter is that we've quickly gone beyond that. For many people now, the most common way to use technology is on a mobile device, and they expect the kind of experience they've become used to on their iOS or Android device to be mirrored in complex software, such as the technology they use for visual discovery and analytics.

From its inception, Qlik Sense has had mobile usage in the center of its design ethos. It's the first data discovery software to be built for mobiles, and that's evident in how it uses HTML5 to automatically render output for the device being used, whatever it is. Plug in a laptop running Qlik Sense to a 70-inch OLED TV and the visual output is resized and re-expressed to optimize the new form factor.

So mobile is the new normal. This may be astonishing but it's just the beginning. Mobile technology isn't just a medium to deliver information to people, but an acceleration of data production for analysis too. By 2020, pretty much everyone and an increasing number of things will be connected to the Internet. There are 7 billion people on the planet today. Intel predicts that by 2020, more than 31 billion devices will be connected to the Internet. So, that's not just devices used by people directly to consume or share information. More and more things will be put online and communicate their state: cars, fridges, lampposts, shoes, rubbish bins, pets, plants, heating systems—you name it.

These devices will generate a huge amount of data from sensors that monitor all kinds of measurable attributes: temperature, velocity, direction, orientation, and time. This means an increasing opportunity to understand a huge gamut of data, but without the right technology and approaches it will be complex to analyze what is going on. Old methods of analysis won't work, as they don't move quickly enough. The variety and volume of information that can be analyzed will explode at an exponential rate. The rise of this type of big data makes us redefine how we build, deliver, and even promote analytics. It is an opportunity for those organizations that can exploit it through analysis; this can sort the signals from the noise and make sense of the patterns in the data. Qlik Sense is designed as just such a signal booster; it takes how users can zoom and pan through information too large for them to easily understand the product.

We touched on the boundary between the computing power and the humans using it in the previous section. Increasingly, we're removing barriers between humans and technology. Take the rise of touch devices. Users don't want to just view data presented to them in a static form. Instead, they want to "feel" the data and interact with it. The same is increasingly true of BI. The adoption of BI tools has been too low because the technology has been hard to use. Adoption has been low because in the past BI tools often required people to conform to the tool's way of working, rather than reflecting the users way of thinking.

The aspiration for Qlik Sense (when part of the QlikView.Next project) was that the software should be both "gorgeous and genius". The genius part obviously refers to the built-in intelligence, the smarts, the software will have. The gorgeous part is misunderstood or at least oversimplified. Yes, it means cosmetically attractive (which is important) but much more importantly, it means enjoyable to use and experience. In other words, Qlik Sense should never be jarring to users but seamless, perhaps almost transparent to them, inducing a state of mental flow that encourages thinking about the question being considered rather than the tool used to answer it. The aim was to be of most value to people. Qlik Sense will empower users to explore their data and uncover hidden insights, naturally.