A Brief Conversation about Data Governance


officer.pngReader: “Woah, woah, hold on a second. Really Mike? - A post on Data Governance? - Don't you represent QlikView!? Shouldn't you be blogging about Business Discovery, Big Data or those sexy Data Visualizations!?”

Mike T: “Easy now, take a moment and breath. <sarcastic>You seem to really know your trendy labels, don't you?</sarcastic> Before we can discover our business, visualize our data or understand if our Big Data's signal-to-noise ratio is even relevant – something more needs to happen. Applications and data are typically prepared from gathered requirements before they are deployed to the masses. However, it is this preparation process that will determine the accuracy, consistency, assurance and overall longevity of the BI solution; aspects commonly overlooked when a proper Data Governance framework is NOT in place.”

Reader: “A proper Data Governance what?!”

Mike T: “Exactly!”



Now that I’ve gotten your attention I’d like to introduce you to my new series on – yes, Data Governance. Over a series of articles I will introduce you to the concept of Data Governance and the common symptoms and problems that arise from lack thereof. I’ll also include an example where an agency of the US Government could have saved millions annually if a Data Governance framework had been in place. With help from products such as the QlikView Governance Dashboard and QlikView Expressor, I’ll also cover solutions and best practices that can help increase data confidence and reduce risk in the key organizational information used to make decisions.


It’s a Problem

Over the course of my career I have seen many organizations quickly adopt a BI solution and jump right into creating reports and dashboards for one or a few specific needs, while giving little thought to the rest of the BI solution and how others may benefit from previous work. So what happens? Another application is then developed with its own requirements, possibly using data and attributes similar to the first. When developed in an independent and ad hoc manner (as with many organization) business models, data definitions and semantics can be stored and defined inconsistently. This causes inaccuracies which only delays decisions as users search for the truth in data. As Enterprises strive to consolidate data and express a need for data repurposing, it becomes critical to introduce Data Governance standards. It’s been established by many analysts that a high percentage of BI projects fail to meet their objectives; siting a variety of issues including failure to implement a centralized data repository, inconsistent data models, little to no metadata management and lack of authority to institute and uphold best practices.



Mike T: So Reader, will you join me in my next post where I will address these challenges and solutions in greater detail? Hopefully, you will see QlikView is much more than just visualizing and analyzing data. It’s about driving decision-making using the right data.


Mike Tarallo
Senior Product Marketing Manager
QlikView and QlikView Expressor
Follow me: @mtarallo

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/)

Richard_Feynman_Nobel.jpgRichard Feynman was one of the greatest physicists of the last century. His work spanned many disciplines and his curiosity drove him to explore and understand a variety of problems in the universe. He was awarded the Nobel Prize in physics in 1965.


Feynman, when facing a new problem, used a very simple approach to solve it. He first asked questions and inquired about the details. After that, he retired to think about it, and when he came back he usually had the solution.


His ability to find the core of a problem and describe it in a simple, yet precise way, was unmatched. The method is summarized (probably by his friend and fellow physicist Murray Gell-Mann) as “The Feynman Problem Solving Algorithm”:


  1. Write down the problem.
  2. Think very hard.
  3. Write down the solution.


Intended as a joke, this sounds like a ridiculously simplified work flow for problem solving. One can hardly think that it can serve as an instruction for how to solve a problem.


But it can. In fact, it is even a very useful approach. Seriously.


It can successfully be used when you build QlikView applications. Then you encounter different problems: Figuring out which data to load, modeling this data and how to write different complex formulae.


Using the algorithm, you will find that the hardest part is the first point – to write down the problem. Or rather – to understand the problem in the first place. Point two and three often come automatically if you’ve done the first point properly. Just formulating the problem in precise words will help you understand the problem.  And understanding the problem is the core of all problem solving.


The exercise of formulating the problem in words, and explaining it to your users or to your peers, will force you to start thinking, which means that you start working on point two. You may even write the first QlikView scripts to test different concepts, which means that you start working on point three.


This only shows that the three points are interconnected and that you will need an iterative approach to get it right. I often start working on all three points in parallel, but all the time I am aware that I need to understand the problem and think hard before I can deliver the final solution.


Some methods that I find useful:

  • Listen to your users. They are the best source when it comes to understanding what the application should do; what the goals are. Which KPI:s? Which dimensions? Discuss with them. Ask them questions.
  • In data modeling, you should always ask yourself what each table or record represents. Which field, or combination of fields, uniquely defines a record? Study the data. Understand the data.
  • Visualize your data model. Draw it on a piece of paper, if needed. Name the tables so that you understand what each record represents. Don’t load a table unless you understand what its content is and how it relates to existing tables.
  • Start small: Just one or two KPI:s and few dimensions. Make sure you understand the data model and its calculations before you expand it.
  • A smoker, stuck with a problem, usually takes a break. He stops working and takes a cigarette instead. He starts thinking. Taking a break in order to think, is a very good habit that also non-smokers should adopt. So, once in a while you should walk away from the computer just to think.

Simplicity. Feynman was a genius.



John Sands

Tag Anyone?

Posted by John Sands Jul 11, 2013

The nature of data is changing. At the moment organizations gather data from many different sources including loyalty cards, machine logs, sensor arrays, and social media sentiment analysis (even if they don’t always analyse the data enough)

But what about the future? I recently read a very interesting book ‘Everyware: The Dawning Age of Ubiquitous Computing’ by Adam Greenfield or, as he puts it, “the colonization of our everyday life” by technology. He talks about the many different ways computing will change and spread from discrete devices to existing within the very fabric of everyday life.


This is happening quickly: soon clothing with RFID (Radio Frequency Identification) tags that let climate controllers know of your preferences in temperature and humidity will be a reality.  Floors that can monitor foot fall and your presence in the room could have advantages such as for the old and infirm - if they fall the floor can sense it has happened and notify the emergency services. As I said, don’t imagine this is all in the future: right now in Japan they have fitted RFID tags in some items of clothing so that when an elderly person uses a pedestrian crossing it keeps the light red for traffic for a few seconds longer.

RFID technology eliminates the necessity for line of sight scanning as the tag itself contains an antenna that can transmit the information to a receiver


Here are some examples of where RFID technology is already being used.



One of the major limiting factors holding back this type of technology has been the lack of enough ip addresses, but with the arrival of IPV6, the next iteration of the internet, this restriction will be removed.  Now potentially everything in the world could have an IP address. Coupled with the way RFID technology is becoming cheaper and more readily available this is a movement that will not go away.  It’s the arrival of the internet of things.Obviously this may raise ethical and privacy issues - very topical considering the recent news concerning the American National Security Agency and the Prism Project.

Organisations are already struggling with the data they hold now and the phrase “we are data rich and information poor” has never been more correct. We are only going to get more data it’s just a case of how we use it. So prepare yourself and make sure the data you hold works for you and gives you the insight to help you make quality business decisions.

For a Business Discovery platform to meet the expectations of today’s information worker (fast response times, high degrees of interactivity, self-service data exploration and discovery) and scale across an enterprise, it’s now widely accepted that the use of in-memory processing is required.  Here’s a quote from our partner Teradata, which comes from a disk-based heritage: “Naturally for the data which is being used heavily on a day to day basis then there will a more than convincing business case to store this data in-memory to deliver the performance which is required by the business” (http://blogs.teradata.com/anz/are-in-memory-databases-the-answer-or-part-of-the-answer/ )


This is no surprise to QlikTech as this is the approach we pioneered 20 years ago, and is now being taken up by pretty much all competing vendors.


However, we sometimes come across claims that visualization tools querying direct to disk-based databases are a viable alternative approach.  To suggest that a deployment that only utilizes a dynamic query to disk approach will meet performance expectations is simply not a reality. While some business discovery providers (including QlikView via the Direct Discovery capability) can directly query sources such as Teradata, it’s important to acknowledge that direct query alone is a) much slower and b) utilizes network traffic in an unbounded fashion. Whilst a direct query capability such as Direct Discovery is a very valuable ‘relief valve’ for access to very large data sets, ALL data discovery providers (including QlikView) recommend the use of a performance optimization layer.  In fact, this is one of the defining characteristics of data discovery software according to Gartner (data discovery is their term for Business Discovery):


”Data discovery tools are an increasingly prominent class of BI offering that provide three attributes:

1. A proprietary data structure to store and model data gathered from disparate sources, which minimizes the reliance on predefined drill paths and dimensional hierarchies.

2. A built-in performance layer that obviates the need for aggregates, summaries or pre-calculations.

3. An intuitive interface enabling users to explore data without much training.”*


The reality is that any BI system meant to satisfy business users has to replicate some or all of the data to deliver acceptable performance. Different vendors take different approaches; QlikView uses its associative in-memory engine (which offers up to 90% compression of source data), other vendors use less intelligent in-memory caches, but all the same, they still replicate data. For 20 years QlikTech has developed an in-memory approach that provides a unique high-performance, associative, intelligent data store. In addition we have developed tooling that very effectively manages the data to allow QlikView deployments to scale to many thousands of concurrent users. Any vendor claiming to deliver genuinely useable, fast discovery without recourse to some data replication in memory (or the use of an in-memory database further down the stack – still a rarity) is misguided.  


Related content: QlikView Scalability White Paper. QlikView Architecture and Systems Resource Usage Technical Brief

*Source: Gartner ‘The Rise of Data Discovery Tools’, 26 September 2008, ID:G00161601

A New York Times article from a few months ago really startled me.  The headline was “U.S. to Be World’s Top Oil Producer in 5 Years, Report Says.” This contradicted everything I had known about the slowdown in American oil production.  So what was the game-changer?

There are several components of the sudden shift in the world’s energy supply, but the prime mover is a resurgence of oil and gas production in the United States, particularly the unlocking of new reserves of oil and gas found in shale rock. The widespread adoption of techniques like hydraulic fracturing and horizontal drilling has made those reserves much more accessible.

Until recently, my concept of oil drilling was like this diagram:oilwell.jpg

Find a pocket of oil buried underground, put an oil well on top of it, drill until you hit that oil pocket, and pump until the well runs dry. But most of the untapped oil in the world is not in nice neat reservoirs. It is trapped inside rock formations that are spread over great distances horizontally. To unlock this reserve, two key technologies are required:

  • hydraulic fracturing or “fracking”: creating fractures in rocks and injecting fluids to force the cracks open and release trapped oil and gas
  • horizontal drilling: the ability to drill horizontally, thus be able to follow the natural direction of the oil and gas deposits


What does this have to do with QlikView? Well, we don’t know who first coined the phrase “Data is the new oil” but it is clear that organizations of all kinds are scrambling to unlock the value of their data. Unfortunately, they are still using old technology that can only drill down into data and unlock small bits of value at a time. This is not only true of traditional BI techniques of creating data cubes (thus limiting users to summary views of the data and preventing them from finding the insights hidden in the details) and predefining drill paths (thus limiting users to a narrow line of thought through a report). This is also true of many of the new generation BI tools that promise “ad hoc query” and “multidimensional drill paths” with snazzy visualizations to boot, but hide the fact that underneath the glamour is the same old SQL query on a single data source.

You may already know about QlikView’s distinctive associative experience, which shows with every click what data across the entire data model is associated and what is not. However, what is often less well known among those looking for a truly intuitive and agile BI platform is the fact that QlikView allows users to have that experience across different datasets simultaneously.

A brilliant example of this was recently shared by a customer speaker at a recent QlikView Technology Summit. Larry Griffiths, BI Manager at Bentley Systems, Inc., works at a software company with a broad portfolio of products catering to the infrastructure engineering industry. Their primary data source was SAP BW. With their existing BI tool, they struggled to enable simple tasks like pipeline and contract reviews for sales managers. They also had other data sources, such as log data that tracked actual usage of their numerous software products. Trying to analyze all that information together was difficult.  After spending a year and half searching for a solution, they selected QlikView.  In the words of the speaker, the breakthrough came when with QlikView, “…within half a day, on a little 4GB VMWare instance, we had pulled in 200 million rows of contract data and usage data.  A problem we haven’t been able to solve for a long time was solved.”

After they deployed QlikView, users from across the company found many ways to extract real value from data, via the ability of QlikView to drill horizontally and ‘frack’ the data for its valuable insights.  For example, the product development group made use of an affinity market basket analysis app, which answers questions such as “what products are used most with what other products?” By doing so, they saved over $2.5 million in software development costs in the last year by dropping unnecessary software integration projects.

They are experiencing amazing discoveries by tying multiple data sources together. The latest effort is combining revenue data from SAP BW with usage data from the application server with training data from their learning management system (LMS). What insights could they extract with this? For one, they will be able to correlate the training level of their user base with higher usage of their software and increased revenue. This gives them actionable insight across the entire company to improve customer training programs, upsell training seats, and increase revenue via better bundling of relevant software and training.

To visualize this with the drilling analogy, other BI tools can only deliver this siloed view of data, which not only keeps data fragmented, but leaves users frustrated and resorting to using Excel to get at the insights they need, which defeats the purpose of the investment in BI. QlikView gives them a holistic view, which enables them to extract maximum value from data.  Isn’t that what we all want?


Click here to watch a recorded webinar by QlikView and Bentley Systems.


Do you have a story of “horizontal drilling” with QlikView?  Please share it below!

As we move through life technology is constantly overtaking us. I think this is one of the best parts of my job at QlikTech as you never get a chance to get bored! One of the most obvious of those is changing mobile technology: last April was the 40th anniversary of the mobile phone. I remember my first mobile phone was a Panasonic transportable. Didn’t I look cool carrying that down to my local bar on a Saturday night?



One thing that brought home to me how widespread the impact of mobile technology is was when my wife, who teaches 10 year old children, said that on an end of term day when children were told they could bring a toy to school (in my day it would have been Monopoly or Scrabble) four children in her class brought in a tablet pc.




These children were demonstrating the reality of the Bring Your Own Device (BYOD) trend.


IT departments around the world are trying to figure out how to live with BYOD (some by putting their heads in the sand).  It must be said that the matter can be complicated by the fact that it varies country to country. In some of the BRIC counties BYOD is much more prevalent because very few companies’ issue mobile tools such as phones and tablets, and arguably because of their burgeoning entrepreneurial spirit. Another factor is that personal smartphones are more function rich than phones supplied by many organisations to their employees, and that it’s a real pain carrying around two phones all day.


These forces are pushing us in the same direction towards having to support the BYOD movement. But let’s not be hasty, what do we need to think about when looking to support employees as they use their own device?


  • Full or partial funding
  • Security, partitioning of personal and work apps
  • Expanding mobile to other parts of business
  • What platforms to support and incentivize


(I will cover these points in more detail during a future blog.)


Now there has been a sea change, CTO’s who historically would say “NO!” when asked to support a personal device are now looking at how they can actually save money by doing so and increase mobile coverage within their workforce.   This is a growing fact of life: Gartner states that by 2016 38% of all organisations will only support BYOD and will actually subsidise employees for using their own device.


What are you doing about BYOD?  What are your experiences?  How does BYOD relate to how you use QlikView?

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).

I watched a fascinating program by VS Rachmandram where he discussed patients feeling pain in ‘phantom limbs’. An example might be pain in an arm that’s been amputated where the person feels their hand is permanently clenched into a tight fist. To solve this problem the brain is tricked by using a simple box and a mirror which makes it think the amputated limb is ok, the hand is open, and the pain disappears.

This serious subject highlights the power of the brain and how powerful visual stimulus is.


There are times when our brain can actually fool us in to seeing or feeling things that are not there. If, for example, we are looking at a chart that’s not well designed we are likely to make assumptions - and we all know how risky assumptions can be.

Further, our brain hasn’t evolved that far away from our distant ancestors, so the thing that really makes a chart or table interesting is if it appeals somehow to our basic instincts:  can it feed my family, gain me an advantage, even make me more attractive!?  (Unlikely, I know.) 

In the world of work, these basic needs are expressed through analogues: hitting your sales target, getting promotion through recognition, or spotting that upwardly trending product. However the information that triggers these appealing insights is too often buried under ‘chart junk’ – stopping you seeing what’s really there. In his book The Visual Display of Quantitative information Edward Tufte wrote:


“Sometimes decorations can help editorialize about the substance of the graphic. But it's wrong to distort the data measures—the ink locating values of numbers—in order to make an editorial comment or fit a decorative scheme.”

So how do we make sure this doesn’t happen? Well, the old acronym K.I.S.S (Keep it simple stupid) applies.  Airport and road signage are a good example of quiet design. They get you where you want to go without most people consciously noticing.


It’s not complicated, it’s not flashy and it just shows the information needed. So when you design your next dashboard always keep in mind why you are doing it.  It’s not usually so you can show the latest info graphic or cool chart type.

I am not saying when you create a dashboard it shouldn’t wow the eyes and excite the brain but, like a super model with a PhD, it must not only be gorgeous but genius as well.


The QlikView Journey

Posted by Erik Lövquist May 23, 2013

As part of my work as User Experience Researcher, people tell me about their journeys of learning QlikView. This includes developers creating their first applications for other people, administrators setting up large scale environments and users of business discovery applications. These journeys describe both what people struggle with and what they find easy when using QlikView. Each journey is unique and extremely valuable for us in understanding how people use QlikView and how we can support their working process in the best way possible.

user research.jpg

A particularly interesting trend I’ve seen is that people working within business, e.g., controllers, accountants and sales managers, can also have roles as QlikView developers at their organizations. Compared to the “conventional” developer who has specific IT or software developer skills, people with a background in business face quite different challenges when learning QlikView. For example, they are often not familiar with scripting or visualization techniques and worry a lot about best practices when designing apps. On the other hand, this specific kind of developers has an in-depth understanding of their business and the needs of their company and colleagues. They might struggle with implementing technical solutions but the applications they create are often immediately valuable to the business.

By understanding our different types of users we can create solutions that help people quickly learn and effectively use QlikView regardless of how they approach it. People’s journeys with QlikView are the basis for one of our most valuable design tools for QlikView.next: personas. A persona is a fictional character that represents core characteristics of real users based on research. Our personas at QlikTech describe behaviors and attitudes that we gather from engagements with large number of existing as well as potential users. When creating these personas, we do not only ask what people want but also observe and interview them to understand how we can support their needs efficiently and effectively.

Our personas give our different kinds of users names, faces and feelings rather than merely being a “type” or a categorization. They provide presence and influence from our users at all stages of the design and development process. The personas cover novice, intermediate and expert users and our aim is to provide solutions that can support them all when learning and working with QlikView.next.

Do you have your own journey to share or seen any similar trends when working with QlikView? Let us know in the comments below!

My youngest son recently turned 10 years old.  And, the sad reality is that in many ways, he doesn’t need me that much anymore.  


In fact, if I wasn’t so unwilling to give up in my role as his mother, I am quite sure that he could manage to get through an entire day without my help.  Thankfully there is a lot more to life than just pouring yourself a bowl of Cheerios. Somebody actually has to make sure that there are Cheerios in the house… and for that matter, milk.


What does this have to do with the business of IT? 


My role as mother is to empower my boys with the tools and resources that they need to be increasingly self-sufficient and to drive toward their own personal goals. As an IT leader, my role has always been to empower the business users and to give them the tools and resources that they need to propel the business forward. 


I had to stand on the step in order to appear taller than my oldest!


Just as my relationship with my boys has evolved as they have grown, business users are much more tech savvy today than ever and it is important that we adapt our methods of delivering IT solutions accordingly. One example of this is happening is Bring Your Own Device or BYOD where business users take on at least some responsibility for self-support of their own technology devices. Another great example is the move toward self-service Business Intelligence where IT departments maintain discipline around their core mission (security, data integrity, scalability, etc.) while business users are provided with tools enabling them to answer their own BI questions allowing them to move at the speed of business.


Gartner’s research note: “How to Deliver Self-Service Business Intelligence” outlines a model for the critical issues that surround delivering a self-service BI capability and includes three key recommendations for IT leaders, all of which we see in organizations using QlikView:


  • Reevaluate long standing organizational models with the objective of creating a stronger partnership between IT and the business. 

    There are several recommendations in the paper including physical co-location of IT professionals with the business as well as changes in organizational structure.  The form that these changes take will vary from firm to firm but the objective should be the same which is to create an environment that fosters stronger partnership between traditional IT roles and business roles. 
  • Establish governance models for certifying business user driven development.

    The reality is that business users already have a long history of developing BI solutions for themselves.  (I myself am a recovering Excel addict.)  However, it is becoming apparent there have been serious business problems caused by the unfettered use of Excel to support critical business processes. Therefore as we empower our users with new self-service BI tools, it is critical that we also put in place the data controls and governance policies necessary to ensure consistency and the integrity of the resulting business decisions.
  • Increase the reach of BI throughout the organization through the adoption of consumerization technologies

    Here the recommendation is to widen the use of business intelligence by supporting all of the ways through which business users may want to interact with the data.  Specifically highlighted here is the idea of moving beyond static reports and enabling interactive dashboards, visualizations and search. 


A point highlighted in the paper which resonated especially well with me as a mother was the idea of giving the right amount of capability to each business user. My two boys are 5 years apart in age and sometimes it is easy to forget that they need different levels of support. The same is true for our business users. Although any business user can gain valuable insight from an interactive QlikView application with only minutes of training, not all users will be able or even want to be able to develop applications of their own. It is important to provide a platform which can deliver capability to both types of users as well as those in between and to help all users grow in how they use BI for themselves.


Learn more about the Gartner research and QlikView’s self-service BI platform here.


I am personally passionate about improving the partnership between business users and IT and would love to hear from you!

  • Are you in IT? How has your relationship changed with your business users over time?  Do you think it is for the better?
  • Are you a business user?  How can IT do more to empower you to meet your goals?

In one of Charles Dickens’ novels, a young English orphan boy named Pip received a large sum of money from an unknown benefactor and was told he would go to London and learn how to become a “gentleman.”  Charles Dickens entitled his novel “Great Expectations”, describing how Pip felt on his way to the metropolis of London. In classic Dickens’ style, things are never what they seem and Pip’s fortune does not lead to a life of comfort and ease.Pip-magwitch.jpg


The theme of Great Expectations came up in a number of different ways on my recent trip to the metropolis of New York City to attend and present at the Big Data Summit organized by CDM Media. The presenters and delegates were a ‘who’s who’ assembly of people whose titles begin with the letter C: CIOs, CTOs, CDOs (Chief Data Officer), and even a CAO (Chief Analytics Officer), from some very well-known enterprises and brands, including American Express, Citi, AIG, Allstate, Suncor, and the National Basketball Association.


I certainly had great expectations going to the event: surely the industry luminaries would have Big Data all figured out and I would be able to come away with a better understanding of Big Data use cases.  The first speaker heightened my expectations – he gave jaw-dropping statistics about how Big Data helps the healthcare industry fight the annual loss of two hundred billion dollars to fraud and how Big Data helps a wind energy company optimally place its wind turbines by crunching massive amounts of weather data.


Another speaker gave an impassioned call to train our schoolchildren in technology and mathematics so they could become data scientists, helping corporations and nations gain a competitive edge.


Three surprising commonalities came out of these presentations and nearly 20 private conversations with these executives:

  • They don’t have Big Data all figured out. Successful projects with large ROI are few and far in between, many are still in the experimental phase.
  • Adoption is low. One executive said, “My problem is getting my people to actually use the expensive data warehouse we bought.” His data warehouse had over 125 terabytes of data.
  • Innovation comes from data mashups. The executives were most excited about the possibilities when internal data is combined with customer data, sensor data, and news feeds to deliver new services that don’t currently exist.


What did exceed my expectations was the high level of engagement the executives had as they learned about QlikView in relation to Big Data. The top reasons were:

  • QlikView helps them walk before they run. When asked if they are making the most use of their existing “small data,” not one person said yes. They saw how QlikView’s Business Discovery platform helps them achieve immediate return on the data they have, rather than waiting years for their Big Data projects to complete.
  • QlikView helps them explore their Big Data. Because creating data mashups is so intuitive and simple in QlikView, they can take extracts from their Big Data source, mash them up with other data sources, and explore the results in real time without the usual query lag and laborious data modeling work.
  • QlikView reduces dependence on data scientists. Everyone who saw a demo of QlikView for the first time was impressed with how intuitive it was to answer question after question simply by clicking, without having to create more visualizations or hire data scientists to do so. Since QlikView can scale from “small data” to Big Data, it uniquely addressed their short and long term analytic needs.


Like a great novel with unexpected plot twists, I entered the conference with great expectations, saw them brought low, but then ended with a fresh excitement over what QlikView can do for the largest of enterprises wrestling with the challenges of getting broad value from both small and big data.

For more information, check out QlikView’s page on what Big Data can do for you.

John Sands

The Key to Associations

Posted by John Sands May 9, 2013

I sometimes get asked to explain what QlikTech means when it talks about association.  Here’s how I explain it…


Too often we are compelled to adapt the way we think to the way software tools work.


This is the case with many business intelligence products, which optimise their performance by forcing us down linear drill down paths. But our brains don’t work in that way.  Our brains work by association.


For example, if we lose our car keys we don’t work through a pre-set drill down path. We don’t think to ourselves, “Hmm.  Let’s see, I was on planet Earth, in Europe, in the UK, in Hampshire, in Portsmouth, in Southsea, on Nelson road, at number 7 and in the kitchen.  Are my keys in there?  No, they’re not!”   After failing we’d then have to start all over again down another pre-set path.  If our brains were like most BI tools we’d probably have to wait for our consciousness to establish a new drill path!


In truth, what we do naturally, is think “What was I doing before I lost my keys? I remember; I was making a sandwich in the kitchen to eat while watching TV on the sofa.  A-ha! There are my keys down the back of the cushion!”  We find or make insights by associating non-linear data points.   (At the same time you might find the remote control you lost or if you’re really lucky some loose change, which you didn’t expect).  Providential discoveries rarely (if ever) occur through over structured thought processes.


We are used to being able to search freely for data quickly across billions of items on the web.  Many users of traditional BI wonder why their BI isn’t as simple as this.  Why do we have to change the way we discover things in everyday life just to suit a set of rules set down by a BI architecture detached from our  working reality?


To give a real life example of this I was trying to book a flight for my family this year somewhere warm and dry  (I live in the UK!) but on a budget. I went to the website of a well-known airline and selected my dates and destinations and then followed the path defined by the website. By the time I got to the 10th step and added all the taxes and baggage costs it worked out to be too expensive.  Wouldn’t it be a much more pleasurable experience if I could enter my budget and dates and automatically get shown the destinations that were available for me? Or a country and budget and see what dates were associated and available with those selections?


Life shouldn’t be that difficult.  We should all be able to just follow the associations.

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?

Every year, QlikTech executes several strategic initiatives. These are cross-functional programs that are funded out of a special budget and are blessed with executive sponsorship from the highest levels of the organization. An example of a QlikTech strategic initiative is QlikMarket, which we launched last year. One of QlikTech’s strategic initiatives for 2013 is called Customer Success.

Customer Success strategic initiative - four pillars.png

This initiative is very exciting for me on a couple of levels:

  • Focusing on the customer first is mandatory. Based on recent research from Temkin Group, most B2B (business to business) companies – whether they are in technology, financial services, aerospace and defense, or any other industry – are still mastering the basics of customer experience.* If in your role at work you deal with people from other companies, you probably see evidence of this yourself. But we live in a world where business customers have high expectations, often set by what they’re used to getting as consumers. B2C companies know that customer experience drives business loyalty. In my personal view, the software companies that will be around in 15 years are the ones that deliver a fabulous customer experience.
  • Your success is my passion. After more than 2½ years in QlikTech’s product marketing group, I have moved into a new role at QlikTech heading up a function called Customer Advocacy. The Customer Advocacy team is focused on measurement and accountability. As you might expect for a company that makes analytics software, we are firm believers that what you can’t measure, you don’t do. So we are launching quarterly customer relationship surveys and putting processes in place to act on your input. We expect the first survey to launch in May. If you see one come your way, please take a few moments to share your open and straightforward feedback with us.

So the focus of my posts here on the Business Discovery Blog will change. Rather than writing about Business Discovery and trends in the BI market, I look forward to sharing updates with you about the Customer Success initiative. Stay tuned.

* See “Best Practices in B2B Customer Experience,” Temkin Group, April 2013 (by subscription or for purchase).

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