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Viking Analytics AB: Viking Analytics introduces the new look of MultiViz: a self-service advanced analytics solution for heavy industrial companies

MultiViz leverages data science and machine learning innovations to enable features that accelerate time to insight and enables the experts to prepare, analyse and process sensor data without being a data scientist. MultiViz turns complex data into value and actionable insights by putting the power of data into the hands of those who understand what it means: the subject matter experts.

Maintenance of equipment is one of the biggest expenses in the manufacturing and heavy industry, but now companies can benefit from MultiViz solution by lowering their operational costs, boosting productivity, reducing downtime, obtaining better visibility, and getting more value from the operations.

MultiViz has a broad spectrum of features that makes it powerful for analysing complex production data and it allows condition monitoring, reliability and process experts to discover interesting events and detect abnormalities in data, perform root cases analysis, predict asset health, fingerprint interesting events, and visualize data.

Rajet Krishnan, CTO at Viking Analytics, said: "We are excited to bring our self-service data analytics software, MultiViz, to asset-heavy companies who have been collecting large volumes of sensor data. The new look and user interface simplify their journey towards actionable insights and business value. It has been specially designed to enable the subject matter experts to perform complex data engineering tasks without being a data-scientist or a programmer. These tasks include performing collaborative root-cause analysis, detecting anomalies in asset behaviour, and operationalizing smart alarms."

Starting at an attractive price, MultiViz is an easy-to-use software that connects to different industrial databases. With MultiViz, the journey towards valuable insights and ROI, both short-term and long-term, have been truly simplified.

MultiViz solution can be run in the cloud or on customer premises.

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