I don’t like clichés, but idioms help us to understand common conceptions (and misconceptions).  As with many sayings, the origins of the idiomatic expression “a picture is worth a thousand words” are obscure.  However, its meaning as it relates to the BI space is clear; it “aptly characterizes one of the main goals of visualization, namely making it possible to absorb large amounts of data quickly”.


The power of visualization is undeniable, and Qlik has always been in the vanguard of using human visual acuity to help us get value from data. I’ve personally written and presented on this for years*, and Qlik continues to build amazing visualization capabilities.


There’s an issue with visualization though – in that it’s only part of the picture!  Charts alone are arguably just better descriptors of data – great for information delivery – but are only partially valuable when it comes to analysis. To be of more analytic use, the visualizations must be fully interactive, paired with and powered by navigation capabilities.  This combination enables the free exploration of the data pictured, and the data not pictured but in the dataset.  (See Curt Monash’s blog ‘Visualization or navigation’ for an independent take on this.)


If visualization is not paired with navigation two things occur.


First, people have to create more and more visualizations to try and replicate an exploratory experience, i.e., to picture more perspectives on the data.  This is not optimal.  It takes time.  Further, while linked visualizations are useful, trying to compare across many different visuals is difficult for people. It’s not uncommon for organizations using visualization tools that lack full interactivity to end up with many hundreds of charts because of this need.  Chart bloat is a problem; reading a large amount of charts is as hard trying to assimilate the meaning of many words.  Academic institutions often limit the length of doctoral theses to 100,000 words.   Assuming the cliché’s broadly correct, if a picture = 1,000 words then just 100 charts = PhD thesis!


Second, and more seriously, if the focus is more about picturing data than navigating and exploring it, then there’s simply less business value to decision makers.  Any initial picture describes the state of data, providing an answer to the ‘what’s happened/happening?’ questions posed by organizations.  Answering the ‘why?’ questions that immediately follow demands rapid iterations through the data, re-picturing it if needed, or using alternative search and navigation experiences, so decisions can be made.


Ironically, I’ll rely on a visual from independent analyst Cindi Howson’s rigorous ‘2014 Successful BI Survey’ report as a proof point here:


Chart from 2014 Succesful BI Survey.jpg

Source:  Cindi Howson, ‘2014 Successful BI Survey’, February 2014, pp40.  Used with permission.


I’m not sure if this picture tells a thousand words, but it certainly speaks volumes (cliché!) about the relative business impact of combined visualization and navigation, given that the BI industry average for delivering ‘significant business impact’ is reported as just 28%.




*For subscribers my 2011 Gartner paper 'Who's Who in Interactive Visualization for Analysis and Dashboarding' may be of interest.

Nope, this isn’t a pastiche on Harry Potter, but a reflection on the reality on how far GUIs can take you.


Wizard.jpgNot long after I joined QlikTech, I attended a dinner with a group of QlikView users.  One of my dinner companions, who’d been using QlikView for a long time, had also been trying out a visualization tool.  He said something about his experience of using the two that struck me as very insightful: “What I can build in QlikView in 30 minutes, I can build in 10 minutes in a visualization tool.  What I can build in a day in QlikView, I cannot build in the visualization tool.”


Based on my interaction with customers and prospective customers in the last few months, it’s increasingly obvious that people are beginning to get it.  In their evaluations they are starting to see past the initial ‘wow!’ of an easily built chart, and comparing based on front-end experience and back-end power.  Without the back-end power of QlikView to speed iterative, unconstrained analysis any front end would quickly lose its sheen anyway – pretty charts count for little if performance is poor, as users won’t or can’t wait.   (QlikView’s strength here was borne out by BARC’s recent BI Survey, which ranked QlikView #1 for query performance vs. other ‘Visual Analysis & Data Discovery Vendors’).


What I still hear however is the comment (usually originating from our competitors) that ‘scripting is bad/outmoded/old-fashioned/too hard’.   Wrong, wrong, wrong.  Scripting is an aspect and evidence of the power of any platform.  QlikView has always been a Business Discovery platform, not a single use tool, and will continue to be so with QlikView.next.


Wizards are great – and QlikView has them too for data integration - but they’re an option for simpler scenarios.  It’s disingenuous to claim that a graphically driven wizard in any software product can facilitate building as broad a set of applications as a scripted development language can.   Any GUI or step-through wizard has to present a small set of options to the user – if not it becomes complex and confusing to use.  As such, at some point users inevitably come up against the edges of what they can do with a wizard: if they don’t, if all of the functionality of a BI product can be developed and deployed via a wizard, then that product must be limited in the value it can provide.  Again: “What I can build in a day in QlikView, I cannot build in the visualization tool.”


Finally, if users cannot build what they want in a simple BI tool due to its backend limitations, then they are going to have to do scripting anyway, just externally to the BI product probably using (yup – you guessed it) custom SQL code, and that comes with its own set of demands and limitations.  Just try writing the SQL to handle OUTER JOINS between multiple tables to display in a viz tool vs. the script to do so in QlikView (LOAD * FROM…).  I know which is simpler - but again that speaks to the power of QlikView’s backend – its associative engine.


For QlikView the answer is wizards and scripts, to access the power of the backend and deliver the widest value via the most appropriate interaction for each type of user.

As a kid I loved to play video games like Defender, Battlezone and Elite.  The games themselves had a lot in common – they all had blocky 8-bit graphics, involved shooting stuff, made loud explosions and used ishiness


Defender caption 2.jpgIshiness? 



Coined by QlikTech’s John Teichman, ishiness means having a quality that gives people the ability to maintain an overall sense of a data set and where they are within it.  (According to John the term’s a corruption of the way we use ‘ish’ as a suffix in English to denote that something’s broadly right.)   Whatever it’s called it’s a fantastically helpful when looking at large or complex datasets.


Below are two examples of ishiness in the pre-release version of QlikView.Next (and of course maybe subject to change as such).  The first is a video of a column chart with a grey ‘ishy’ window below it, showing which part of the overall data appears in the main visual.   It’s a simple idea, but very effective, particularly when paired with interactive selection methods, like those shown in the second half of the video.


The way it works reminds me of the side-scrolling maps in old video games, which gave orientation and situational awareness clues to gamers.  To put my old Gartner hat back on for a minute, I suppose you could say that ishiness is one aspect of the ongoing gamification of analytics.


The second example video shows what happens when zooming and panning a scatter plot.  Note the small dots that appear and move around the borders of the chart.  Without these small ishiness dots which appear around the main visual it would be all too easy for people to forget where they are in the data overall.  In other words to lose the ‘information scent’ they were following and most likely the insight they’d make.


QlikTech’s been thinking about this need for orientation within data for a while now, and it could be argued that the mini charts that can be put into tables in QlikView11 show some ishiness too


Capabilities like this are important - as the datasets people want to assimilate and analyse get ever bigger the analytic software we use has to help us navigate and orient ourselves in large information spaces easily and quickly.  Ishiness is one aspect of the natural analytic capabilities that do exactly that.


Oh yes, and it happens to be pretty cool too.  That’s ishy, man.

I was talking with my ex-colleague Dan Sommer from Gartner on the train heading to Schiphol airport after we presented at the Business Discovery World Tour (BDWT) event in the Netherlands, when I noticed the young guy sat next to us was interested in our conversation.


He was nodding and smiling and then told us he’d been at the event and how he’d come to be a QlikView user and champion.


Evoluon with caption 2.jpg

Three years ago people in his company were struggling to do analysis of their business data with a mega-vendor BI tool.  So far, so normal.  At this point our young friend took the initiative. At home over one weekend he found QlikTech on the web, downloaded QlikView personal edition and learnt how to use it on some data of his own. He also used information from QlikCommunity to help him do so.


Here’s the key thing: the reason he did this at home was that he could not do so at the office.  His employer’s systems were locked down and it was forbidden to download and install any software.  However, he didn’t accept the status quo and found a solution for himself and, after showing them what QlikView could do, his company.


In doing so he demonstrated two key trends we’ve been talking about at the BDWTs – the rise of user information activism, and to a degree, BYOS (bring your own software).   Three years later, QlikView is a standard in his organization, used by many and managed by IT.


Did you need to do the same and be an information activist to get QlikView into your organization?



(If you’re the person we spoke with briefly on the train please feel free to comment.  I’m sorry I didn’t get your name when we met, as I found your story very interesting and relevant…)

Recently, I was fascinated by a story reporting that the artificial intelligence (AI) in a computer game had independently identified the futility of war: a “user set up a Quake 3 server with 16 AI bots on it, and left it running in the background for four years. Because the bots learn to re-use successful tactics, he was intrigued to find out what they'd taught each other in the 35,000 hours they'd been at war... In fact, they weren't fighting at all. Instead they were standing peacefully, watching as he walked around each map… [the] bots took less than four years to discover what humanity has failed figure out in a fair few millennia.”


Sadly the story turned out to be untrue.  But it started me thinking about machine and model-led decision making, and the critical importance of being able to think differently to compete effectively. 


As a child I was a fan of the long-running TV sci-fi show Doctor Who (geeky, I know).

In particular, I recall one plot in Police Box with caption.pngwhich the Daleks were at war with the Movellans (a particularly funky android race with silver dreadlocks – well, this was the 1970s…).


As purely logical technological beings neither side could outthink the other.  They’d programmed their “battle computers” so similarly that stalemate ensued as the computers spent years failing to come up with a winning strategy.  Unlike the supposed Quake 3 bots though, they didn’t simply hang up their lasers and declare peace.  Nope, they looked for a source of intuition and fast original thinking to break the deadlock, by co-opting the Doctor or, in the Dalek’s case, going back to their biological roots.


Now, it may be unfair to equate SAP to the implacable, inflexible Dalek race, but if companies using ERP apps implement their battle computers business intelligence platforms starting from the same pre-defined business schema, and those top-down models are rigid enough to restrict humans’ ability to think creatively, are they really helping them compete? 


I suppose it’s also unfair to compare Oracle with the soulless, unoriginal Movellans, but if you implement prebuilt BI apps on the same conformed dimensional model and use the same out-of-the-box reports as your competitors, aren’t you doomed to act within the same prescribed mind set as them?


In contrast, to help their organizations compete what decision makers really need is unfettered analytic creativity.  Creativity through technology so that they can analyse, compare and anticipate beyond standard models, question assumptions and make intuitive leaps wherever the data takes them. Perhaps that’s another reason why many BI customers are looking to business discovery and QlikView for help.

Sports play an important role in building a cohesive and inclusive society, capable of uniting people from diverse cultural and religious backgrounds through playing or supporting sport together. Ultimately, we love to cheer on our compatriots and favorite athletes to success, or to see how, by improving their performance, the underdog can come out on top.  That’s why we can understand the widespread excitement and huge following for the Superbowl in the US, the Champions League football final in Europe, the Tour de France in the Alps, and, once every four years, the global games that are the Olympics.

True sports fans know the history of their sport; who the most successful and least successful players or athletes are; which year they were most successful; how many games or matches each participant has won or lost.  The fact is, when you enjoy something, it’s easy to learn about it.  Of course, the same goes for the athletes and their management and sports teams – they know the history.  They know who has been strongest over the years.  They know who made errors, what the competition is likely working on and what equipment is being used.  However, increasingly fans and professionals are pushing their understanding further and learning more through deep data analysis.

Sports enthusiasts and professionals will tell you that they have been analyzing historical data and looking for new opportunities for years.  It’s only with the emergence of new analytic technologies, tools and techniques that it has almost become widespread.  Further still, the statistics around games have become ‘gamified’ themselves – consider fantasy leagues or online or console games, where fans can play at and learn from being a manager trying to create the most successful team via the manipulation of a set of facts and statistics.

Back in the real world – to do great analysis of any sport you first need access to data in a structured and coherent form.  Beyond that you need an intuitive, user driven analysis experience that allows users to explore the data and make discoveries seamlessly. With the PGA and European Tours in full swing, QlikTech has created a Pro Golf App that lets everyday users (and golf enthusiasts) visualize, analyze, compare, and contrast tour data from 2004 through the latest tournament scores this year, as well as World Ranking and FedEx Cup Ranking.  We’ve previously done the same for the 2012 Global Games, the Grand Prix, and many more sporting events.  Thanks to the availability of data, the rise of fast-speed internet and social networks to share insight and the ability to access information on the go with mobile devices, with the Pro Golf App sports enthusiasts can explore the data by year, player, tournament, country, and more and ask questions such as:

- What percent of tournaments played does Rory McIlroy win?

- How many tournaments have South Africans won this year?

- Which German golfer held the No. 1 ranking for just two months?

- Which four countries account for 78% of the major championship wins?


golf shot 3 Analytics as a Game in the World of Sports


Nothing gets a sports fan going more than when someone disagrees with a fact about their favorite player, team or country, or relays information that they don’t believe.  With the availability of data and the tools to unearth a key fact, statistic, or comparative piece of information, the amount of collaboration and debate around sports analytics has risen hugely in the past few years, there have even been Hollywood movies about it!  The challenge is to understand the best way to present this data to the players, coaches, media, and fans and extend our enjoyment of the games even further through analysis and discovery.


(This is a repost of a blog published recently in http://www.itbriefcase.net/)

Shall we play a game?

What word can connect all three of these words?




Here's a picture to give you time to think - be warned though, looking at the picture may stop you finding the answer (more on this below).



Got it? That’s right; ‘apple’ can go with them all: pineapple; crab apple; apple sauce.

There are two ways of coming to the answer:

  • Analytic logic: did you run through a series of possible matching words until you found the right association? For example, saying: “Does ‘cake’ work? No. Does ‘cone’ work? No. Does ‘tree’ work? No. Does ‘apple’ work? Yes.”
  • Unconscious Insight: did you have a moment of pure insight, where your brain leapt to the right answer? You somehow just knew it, with no conscious thought process?

Humans do both, but the neurological process that drives insight, those amazing a-ha moments we all have, has been little understood until recently.

Neuroscientist Dr. Mark Beeman at Northwestern University is using puzzles and brain imaging to understand how insight works. His team have discovered that when an insight occurs different areas of our brains are active than when we reason analytically. The research has identified that a part of the brain above our right ear (specifically the anterior superior temporal gyrus) emits an intense burst of gamma brain waves when an insight happens. As Dr. Beeman says, “The dendrites – the pieces of the neurons that collect information - actually branch differently on the left and right side, characteristically having broader branching in the right hemisphere, so that each neuron is collecting information from a broader source of inputs and this allows them to find connections that might not be evident otherwise.”

So, here’s objective evidence of association occurring naturally in the brain, making connections between distant concepts, in a flash of insight. It seems that associative technology really does reflect the way that we think when we gain insight.

Interestingly, given all the attention on visualization at the moment, neuroscience research has found that although insights can be prompted by visual cues, the brain activity that generates insight is explicitly non-visual. As Professor John Kounios at Drexel University explains: “At the a-ha moment there’s a burst in the right temporal lobe… but if you go about a second before that there’s a burst of alpha waves in the back of the head on the right side. Now strangely enough the back of the brain accomplishes visual processing and alpha is known to reflect brain areas shutting down.”

In other words just before an insight the brain closes down part of the visual cortex.

“You have all this visual information flooding in; your brain momentarily shuts down some of that visual information – sort of like closing your eyes… so the brain does its own ‘blinking’ and that allows very faint ideas to bubble up to the surface as an insight”. Prof Kounios continues: “Think of it this way – when you ask somebody a difficult question, you’ll often notice that they’ll look away or they might close their eyes or look down. They’ll look anywhere but at a face which is very distracting. If your attention is directed inwardly then you’re more likely to solve the problem with a flash of insight.”

The key point here is that while visualization is very useful and compelling, used in isolation (or too extensively) it’s not the most powerful driver of insightful thinking.

Time for one final game: what word can link these four words?





Got it? I’m sure you have. So what was it for you, analytic logic or pure insight? If it was insight did you catch yourself looking away so your brain could blink!?


Notes: 1) This subject of this blog and the quotes in it came from a fantastic BBC Horizon documentary. 2) I’m aware that the word puzzles in this blog may not be as effective for readers whose first language is not English - I hope that doesn’t undermine its interest for those of you. 3) Distracting image source (creative commons sharealike license).

Gartner recently published a new research note called ‘Market Trends: The Collision of Data Discovery and Business Intelligence Will Cause Destruction.’ (Data discovery is Gartner’s term for Business Discovery.)
A helpful team of operatives stood by to produce reports and make changes to the old BI platform’s semantic model…

The Gartner report sets out two possible scenarios:


1) "Data Discovery Becomes a Feature." In this scenario, Business Discovery would become subsumed in broad BI platforms as traditional BI vendors copy or buy lookalike functionality.


2) "Data Discovery: The Leading New Analytic Architecture". According to the report, "In this scenario, data discovery muscles out and replaces the BI platform for a majority of analytical/diagnostic use cases."


In this second scenario Gartner highlights a key shift in priorities "Whereas previously, users were looking to have a portfolio of: (1) a BI platform (semantic layers providing the end-to-end spectrum of reporting, ad hoc query and OLAP functionality); (2) data discovery in a tactical fashion, adopted individually or in workgroups; and in some cases (3) statistical/predictive analysis tools; the selection criteria has shifted to look like this: (1) data discovery (now the central norm for analysis on all data sources, and where most BI budget goes); (2) production and external reporting tools for systems of record; and (3) additional statistical/predictive analysis capabilities."


Business Discovery is now being viewed by industry analysts as a viable mainstream alternative to traditional BI, which should prompt thinking about the investments organizations are making to meet their analytic needs. Do they want to continue to spend the majority of their BI budget on top-down reporting led approaches, or switch over to user driven discovery and diagnosis? For many QlikView customers, Business Discovery is already the "Leading New Analytic Architecture."


Gartner gives no indication as to which scenario it expects to prevail in the long term.


It’s obvious what QlikTech believes will happen.


What do you think?

I’ve been an advocate of the consumerization of BI for a number of years. Business Discovery platforms like QlikView that embody consumer oriented characteristics are more acceptable to a broad range of people, and so see higher adoption. At core, the consumerization of technology is about empowering people to do what they need, themselves. To be able to do so any technology must possess the three key consumerization attributes of speed, usability and relevance. (For more on these see Jeff Boehm’s 2011 post on my definitional research note whilst at Gartner).


However, driving back from taking my children to school on Tuesday morning I heard a discussion, on BBC Radio 4’s Today programme about the 2013 UK Design Awards, that brought home to me that there’s a fourth attribute of consumerization, as important as the others: aesthetics. For some people how something looks or feels will overcome the three other consumerization attributes, no matter how strongly they’re made available. It’s worth noting that while usability and aestethics are closely related they’re not the same. Something can be very usable, but not look pleasing. I suppose that’s the difference between satisfaction and delight.


During an interview on the radio show Professor Josh Silver, of the Centre for Vision in the Developing World (CVDW), described the Child ViSion self-adjustable glasses his organization is distributing through schools. The glasses have fluid filled lenses that are adjusted using pre-attached syringes. 



The glasses are a powerful example of the consumerization of an established technology:

• They’re fast; adjusting the lenses to correct someone’s vision takes a few minutes at most. 

• They’re usable; each glasses wearer self serves by fitting their own specs – no optometrist needed. 

• They’re relevant, directly to the individual life chances of the person that gets a pair, and broadly to the estimated 60 million young people that suffer from uncorrected myopia in the developing world. 


Crucially though (and unlike earlier versions) the glasses are designed with aesthetics in mind. Their shape is pleasing. They come in a variety of colors. The syringes on the arms used to alter the focal length are easily removable. Why does this matter? Because the target group for these specs is 12 to 18 years old! Image conscious teenagers the world over won’t wear something that doesn’t look good, no matter how useful it is. I’ve personal experience of this – when I was at school the UK National Health Service (NHS) provided one style of glasses frame in black for children. Nowadays these NHS specs, my 16 year old son tells me, are the height of ‘geek chic’. Back then, kids would do anything not to wear them, even if they couldn’t see the teacher’s writing on the blackboard from their desk. That’s why my short sightedness went untreated until I learnt to drive…


We can learn lessons from the development of CVDW’s inspirational project. 


It’s obvious that QlikView embodies the three attributes of speed, usability and relevance directly in how the technology works. The fourth one, the crucial aesthetic element, is largely up to the people who design the QlikView apps. It’s up to you to appeal to the consumers in your organization through the pleasing design of the apps you make available. Beautifully designed apps, styled to the users in question – a web site analytics apps for marketers should embody a different aesthetic to one for financial analysts – mean higher adoption, better perception of value delivered, greater return and more questions answered. The opposite means a less focused outcome.


A final thought on the Child ViSion glasses project: it’s a massively disruptive technology and extremely cost effective compared to the long established way of doing things. Sound familiar?

Sometimes you have to practice what you preach. Last month I wrote and delivered the keynote at Gartner’s European BI & Analytics Summit, during which I challenged the audience to make some important decisions, and to choose a new path for BI. Well, I’m doing exactly that, by joining QlikTech.


Two paths in a wood.jpg


Some people have asked me, “Why go and work for a software vendor?” Well, I enjoyed my six years at Gartner. The analysts are great, and Gartner’s research remains fiercely independent and objective – you might even say that some of the analysts take pride in their robust dealings with vendors. (One analyst even said to me that if my first Magic Quadrant didn’t get escalated to Gartner’s ombudsman arbitration service by at least one vendor, then I wasn’t doing it right!)


But although I enjoyed being a critic, I recalled the excitement of being an actor. From my time in software development, and later at Hyperion, I remembered the excitement of helping to create and market technology, realized that I missed it, and so decided to go back to working for a software vendor.  But there’s more to it than that – it’s also the realization, made endlessly clear to me when talking to organizations about their BI strategies for Gartner, that the balance of power in the world of BI and analytics is about to tip, and I want to be part of the force that makes it do so.


As a follow up question – and knowing that I’ve had frequent dealings with almost all the BI vendors in the last few years – people then ask, “Why QlikTech?” I answer them with a question: “Do you remember what the BI market was like before QlikTech began to disrupt it?” The market was growing in revenue terms, but moribund in many other ways. It was seriously lacking innovation and was more known for failed projects than successful implementations. QlikTech changed that: It’s a rare thing to find a company and product that completely shakes up a market to the point where the existing market share leaders have to begin emulating its approach, and a bunch of new vendors emerge to follow its lead.


That’s all good, but QlikTech must continue to change the market; it remains a fact that too many people are still working with BI that doesn’t deliver, and they need to revisit how they do it. But for QlikTech to get as many organizations as possible make such shift, it will need to change, too, growing its platform capabilities and extending its reach. The company’s vision for “QlikView.next” (the code name for the next generation of QlikView) sets out how it intends to do so.  QlikTech’s plans are bold, and key in why I chose to join the company and to contribute my energies to transforming how people do analytics through discovery.


So, that’s why I’m here. I’m hoping, in the words of the Green Day song, that the move is “something unpredictable but in the end right.” I hope to have the time of my life.




Image attribution: http://www.flickr.com/photos/swimparallel/3455044234/sizes/l/ (Creative Commons ShareAlike license.)

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