The Associative Difference is about the dynamic experience the user has with the BI application. It's about answering that next unanticipated question. It's about exploring ALL the data freely, in any direction without any predefined paths and with no data being left behind. It's about quickly finding new discoveries where all data sources are important. There isn't any one emphasis on one particular data source such as being labeled primary or secondary like with sql-based query tools. It is also one of the many facets that makes Qlik unique. Yes, the Associative Difference could be imitated by other software and if so, I'm sure the work involved is not as inherit as it is in Qlik. With Qlik it is automatic. At previous companies I even tried to imitate it and it took a lot of work and I still could not get it right. Oh and BTW, imitation is the sincerest form of flattery so thank you, I digress, let's continue.
I close my eyes, my brain is an enormous database and without any visual stimulation to help me, I ask myself the question: What is my favorite apple? Golden Delicious pops into my head. Now, even though I know the answer immediately, my mind has collected enough data over the course of my lifetime to process and come to this conclusion. My decision is based on a combination of senses such as sight, smell, taste and texture. Over time, I have satisfied each one of these senses by querying the various combinations of flavors, textures, varieties and colors until I found my favorite. In BI terms, these criteria can be seen as Dimensions – the textual and descriptive component used to find my favorite apple.
The mind is processing various bits of data naturally from its years of information gathering and its surrounding context. It is inclined to ask more and more questions until the user is satisfied that enough information is received in order to make the correct or desired decision. Note that these questions are not predefined or prescribed however; they are freely formulated based on previous results and can be asked in any order.
This process is the basis of Qlik's Associative Difference.
The Power of Qlik's Associative Difference
I open my eyes…I now imagine I am able to visualize and interact with this data and its surrounding context in a single location, a QlikView application. I visualize the dimensions I associated with the apple: its varieties, colors, flavors and textures. Possibly, another category is available for comparison such as vegetables. Measures, the numerical component of the data, are introduced and automatically calculated and aggregated on the fly very quickly - displaying how many are grown or consumed in each region. I can further analyze this information using a variety of filters that show all related selections while still retaining the ones that are unrelated. At first it appears to be akin to a traditional BI dashboard, but with traditional BI a linear approach to analyze data is commonly used. For example, with traditional BI, once values are selected or filtered, the surrounding data and other context that either may be related or unrelated is lost; removing any possibility of making new discoveries, not the case with QlikView.
So, with Qlik how do I visualize and maintain the aforementioned associations similar to those that were previously formulated within my mind? The answer is Qlik’s associative difference visualized with green, white and shades of gray. By starting anywhere in the application and simply selecting one or more visualizations or list box values, all other visualizations, selections and aggregations dynamically update based off of that selection without losing surrounding context of the un-selected data. Selected data is highlighted in green, related or associated data is highlighted in white, unrelated data is highlighted in dark gray and with Qlik Sense - possible related values to the current selection that are not being viewed are highlighted in light gray. This gives the user an overall picture of the relationships in the data - quickly and easily. I can simply see all other surrounding dimensions and their related or unrelated values based off my initial selection. This allows me to ask that very important next, non per-determind question. Selecting yellow and crisp from the select boxes – not only shows me what fruits are yellow and crisp but also what vegetables are yellow and crisp too – the selections in white. I have made a new discovery. I have found vegetables that might appeal to my texture and color preference. The power of Qlik's Associative Difference helps guide me to my respective decision as well as prompts me to ask the next question that possibly I did not anticipate – such as which yellow and crisp vegetables might also appeal to my taste. The power of Qlik's patented Associative Engine specifically lets you experience interactive, free-form exploration unlike what you would get from relational databases and SQL queries which were not designed for modern analytics.
Qlik delivers the world’s first associative difference. It manages associations among data sets at the engine level, not the application level and stores individual tables in its associative engine. Every data point in every field is associated with every other data point anywhere in the entire schema allowing users to quickly and easily explore data freely and answer that very important next question.
So there you have my perspective on the associative difference. Tell me what you think.
Senior Product Marketing Manager