Just a couple of weeks removed from the Trends 2018 Webinar, I was truly surprised by the number of people who registered and attended. In case you missed it, you can view it on our webinar registration page. We got a ton of questions, nearly 100 of them in fact; too many to summarize in a blog. Most of them were answered privately. There is, however, room to highlight some that I either got multiple times, or which I found particularly interesting:
A1: This is an excellent observation. To a certain extent, it does. But it also complements it, because you also need context. I've used maps as an analogy in the past. When we were small, and travelled with our parents in a car - they needed a thick map book, which you had to browse to find the right page. As GPS technologies evolved, you now had the right context on a screen on your dashboard. And in some cases, it's enough to have a voice, and an arrow pointing to what you need to do next. However - we still want to have our screens that we want to zoom in an out of, because it provides much better context to the data point of where we are at. The only difference is that the visualizations have become more contextualized and accurate. I think with voice and narrations, it will be the same thing. You might be able to have a conversation with your data, which gets you to you right answer. But then you might want to ask how that answer relates to a broader context, by saying "show me how that relates" or (doesn't relate for that matter), which puts the answer into a contextualized, associative visualization. What I think will change is that the finding will drive further visualizations, rather than visualizations trying to render a finding.
A2: Qlik was one of the first vendors in the analytics space to build a bot, and the good news is that we've just put them on Qlik Branch, for anyone to leverage. Visit our community to learn more about Qlik Insight Bot.
A3: Great question. To me they overlap. Analytics can be without visualization, and visualization can be without analytics, but great tools have both. I think this is where most visualization vendors fall down. Qlik is a data discovery tool in which you can do analysis in the application, which is displayed through dashboards, visualizations, and increasingly text/voice. The analysis is in the discovery and the workflow. Hence, the easier the tools are to work with the more analysis you can do, because the workflow becomes easier in ingesting, combining, analyzing and communicating with data. Of equal importance are the analytical apps where you can also do discovery/analysis, merely as a consumer. But because of the associative model, the discovery, interaction and analysis is still strong. Or, a finding can be brought into the workflow of where you are, which is still analytical if it's highly contextualized, because it meets the user where they are, in their "moment" of decision.
A4: Qlik is addressing those trends head on.
A5: You'll see more and more machine learning capabilities offered by Qlik in our engine and insights board. Our technology is augmented as we innovate UI paradigms, and experiences that bring the human and machine together, that use:
Our vision is not only about “the machine augmenting the user”, but also “the user augmenting the machine”: Qlik’s Cognitive Engine learns from the user’s interaction with the data, and it is contextual. This is how it generates specific, relevant insights for a given user’s analysis intent.
Our Big Data Indexing and the Cognitive Engine will ultimately work together in the future to generate associative insights for the users with Big Data.
Our unique interactive, selection based UI will enable this; to learn and know more about user’s intent.
Our technology is Associative: Associative Indexing addresses the need to create enterprise-wide schemas that support the full integration of all data assets.
Our technology is Intelligent: Qlik cognitive engine leverages advanced algorithms and machine learning to provide insights to broader range of users.