The new MultiViz is here!

When we founded Viking Analytics in 2017, our mission since day one has been to put manufacturing data – and all its possibilities – in the hands of professionals that know the most about the production lines, the processes, the machines. Our self-service data analytics software, MultiViz, became the embodiment of this mission.

Three years on, as we launch MultiViz 4.0, we see that while it was not set out to be a tool for data scientists, its unique combination of features makes it work for data scientists, managers and domain experts as well. It raises the common understanding of the data, its insights, and possibilities, so decision making in groups can be based on shared facts rather than single individuals.

Another shared goal in the development team was to build the product in a way that users could work with data without becoming bored by it. We do it by facilitating and speeding up the process of going from time-series data to insights. Historically, there are many tools that do this, like time-series plotting tools, Excel, and Matlab. Recently machine learning has become popular, enabling new algorithms that process data and/or predict stuff to essentially create more insights.

MultiViz combines the above together with a unique user experience (UX) that simplifies data exploration even further. It breaks away for the “waterfall” method of other tools. No more data exploration is done in a linear model (get data, prepare it, then explore, then run/train algorithms). Instead it all happens (almost!) at once. The users quickly get from wanting to analyze new data, for example from an anomaly in their production, to actual data exploration. And while exploring their data, insights are saved, powerful algorithms run in the background and the user’s knowledge gets integrated into the data.

New features for a more productive day at work

As much as we talk about exploring data and going on a data journey, in the end of the day, what we give to our users is a better day at work, with less time spent on boring tasks, more quality and productivity and greater collaboration in teams. And MultiViz 4.0 brings this in the form of our new functionalities: Tag Assistant, Virtual Channels, and the improved Analysis Log.

  • Tag Assistant makes it easy and fast to explore datasets with 100+ channels. It lets the user simultaneously handle hundreds of tags, split the data into separate views for easier and faster data exploration, and switch between views to quickly explore different parts of the process. The Tag Assistant also incorporates data preparation and relieves the user from having to do it.
  • Virtual Channels are predefined functions that insert additional channels to the data. It enhances data exploration, making it a breeze to find correlations between different channels.
  • The Analysis Log has been improved to simplify and make logging of insights during data exploration more powerful. With it, MultiViz captures domain expertise and makes it available for the future and for sharing.

In this release of MultiViz we focused on overall improvement to the user experience with the new functionalities but also with changes to the project page, data exploration page and case study log. We worked closely with many reliability and process engineers to understand their pain points. By doing thorough UX research we decided what functionalities would bring more benefit to our users.

And none of this would be possible without the most talented and dedicated product team: Nadja Niegel, Rickard Claeson, Martin Fredriksson, and Vishnu Nadhan. Thank you all for your hard work in bringing this new version to life!

And what’s in store for future versions of MultiViz? AI assisted labeling, enhanced multi-user collaboration, and much more. But for now, if you want to try MultiViz 4.0, click here and request your demo.

Johan Isaksson

About The Author

Johan Isaksson is a programmer and co-founder of Viking Analytics. He has a long and broad experience in software product development. He has a MSc in Computer Science and Mathematics from Chalmers University of Technology, Sweden. He is an entrepreneur and has co-founded successful product start-ups. He is an alpine skier, science fiction, AI, tech and science enthusiast.