We are really pleased to be able to publicly announce development of version 2 of QVSource!
The new version is being written with a html front end which means that QVSource will be web hostable, opening up a powerful new set of options for deployment and usage, particularly in conjunction with the new Qlik Sense and also for existing customers running the product on their internal networks.
Due to the way QVSource is built, very little rework should be required on the connectors themselves meaning that changes to the generated QlikView/Qlik Sense load scripts should be minimal to none.
The UI should also remain very familiar (although we expect that using html should open up new ways of making the interface more clean, intuitive and helpful) and this means that the learning curve for users transitioning to the new version should be very small too.
Below is an early screen shot (running on an iPad!) and we are really excited about the future for QlikView, Qlik Sense and QVSource.
If you are an active QVSource user and would like to be involved in providing testing and feedback of the new version we would love to hear from you.
Step Back for a Minute
I have been hesitant to write my thoughts on the new QlikView platform. This is partly because I wanted to be sure I was adding something insightful or at least interesting to the conversation. But, more importantly because I wanted a chance to temper my knee-jerk response with some thought and perspective. On the first point, I am still not sure I will be interesting nor insightful. On the second, I think I have stepped back far enough to see the big picture on what is a large step forward in the evolution of Business Discovery.
With the advent of increasingly larger sources of data it is becoming even more difficult to view or imagine patterns within these data sources. This has become very important in areas such as science; the Genome project for example identified 2,000,000 Genes in the Human Genome, imagine looking at that as a series of numbers.
In 2013 Greg McInerny, Senior Research Fellow in Information Visualization for the Biological Sciences at Oxford University attempted to do some research on how visualization is used by scientists. There is an excellent blog on this published by @FutureEarth. Scientists are inherently skeptical of visualizations. Moritz Stefaner referred to it as “Dumb Blonde Syndrome” the idea that if something looks good, it is suspect. But even skeptical scientists are coming round to the idea that visualizations have their place in detecting patterns and outliers within massive amounts of data.
The visualization above shows the structure of a molecule. This would be impossible to view with the naked eye and can only be viewed by rendering a visualization utilising huge amounts of data. But its not just a case of taking huge amounts of data and creating a pretty picture, the following example proves the point.
It is impossible to view all of the slices and don’t even start to work out the percentages.
A good visualization becomes even more important when the stakes are really high. In the pharmaceutical industry it takes on average 12 years to take a drug from discovery to market and the process can cost around $4 billion. Only 10%-20% of new drugs make it to market and at any point the process can fail either due to adverse patient reactions or the drug just not being as effective as first thought.
You can imagine anything that can increase the likelihood of a drug getting to market is embraced. Data visualization can allow Researchers and Data Scientist’s to explore hugely complicated data sets and also then relate discoveries to non-technical audiences such as investors and regulators by using story telling.
What this says is that although we concentrate on specific subjects such as, Visualizations, collaboration, and storytelling none of these can work in isolation. The scientist will not trust the visualization without data and you can’t rely on data on its own without collaborating with your peers. So what you need is a harmonic join between the three factors.
Please don’t think I am trying to simplify things there are obviously many more pieces involved in this complex puzzle. But as the heat is turned up in the visualization arena and battle is joined between the main players, we will see the creativity of many a web developer let loose on even more and more fantastic visual delights. But embrace the scientist in you and look for substance in that style.
@QlikJohn2014-08-14T08:23:00Z 1 month 3 days ago 0 http://community.qlik.com/blogs/theqlikviewblog/comment/blinded-by-science http://community.qlik.com/blogs/theqlikviewblog/feeds/comments?blogPost=3880 http://community.qlik.com/blogs/theqlikviewblog/2014/08/14/blinded-by-science