In this blog post I’m going to write about a famous piece in visualization history. How can we prove that a visualization is more worth than just looking at the data? That’s a question Francis Anscombe probably asked himself when he back in 1973 constructed the dataset that became known as Anscombe's quartet. A dataset he could use to show statisticians how wrong they were thinking that “numerical calculations are exact, but graphs are rough."

Every time a new Gartner Magic Quadrant is published, I always have a flashback to the scene in the old Steve Martin movie “The Jerk” – when his character gets overly enthusiastic about seeing his name published in the new phonebook. As a software vendor, I think we sometimes look like this when the Gartner MQ is released, and everyone gets a little too excited.

Sometime ago, when I was with another software company, I was involved in a large implementation of our software. The deployment required our software to connect with a legacy customer application, so an integration between the two products had to be developed. When the Sales person put together the proposal, he quoted this integration for $0 because “it’s so simple, I could create it myself”.

AI and its enabled tools continue to enthrall business with its promise of efficiency and innovation. But, one of the things AI is also clearly enabling is the bias. We’ve all read the news and heard the scaremongering stories around potential flaws and biases in Artificial Intelligence systems. I believe for this technology to reach its full potential, addressing bias will need to be a top priority.

Today I’m going to do something different and not talk about a specific visualization as I’ve done in my last blog posts, but rather a technique that we use within visualization. How to create multiple views that each show a different part of your dataset?

We are halfway through 2019 and with the third release of the year, our momentum remains strong as we continue to deliver significant product innovations for our customers across the Qlik portfolio.

I clip in and drive down on the pedals with all of my energy, legs turning and lungs burning as my heart rate soars during this cycling test. I continue to push my limits during this eight-minute, all-out effort. Why would anyone put themselves through such an exercise? The answer is testing. It is a great method to determine the current baseline, establish targeted areas for development and set milestone events.

Today at Qonnections we outlined new innovations in multi-cloud and augmented intelligence that are setting the stage for Qlik as the leading platform for SaaS-based analytics. Leveraging our unique Associative Difference and Kubernetes-based architecture, Qlik is now able to deliver the full Qlik Sense Enterprise product on Qlik Cloud Services.

Qlik has been hard at work the past year transforming its customer success and support organization to truly align with customer needs in a SaaS first world. Today at Qonnections we announced a series of enhancements that put the customer at the center of everything we do at Qlik.

It’s a big day here at Qlik – we officially welcome Attunity into the fold after the formal close of our acquisition. Over the past year we’ve been executing on a vision of what customers truly need from their analytics partner – an enterprise-level data management strategy that fuels enterprise-wide analytics.