Glassbeam, Inc., the machine data analytics company, announced two revolutionary product enhancements for the IoT analytics market. Glassbeam Studio™ an the IoT industry data transformation and preparation tool focused on automating cumbersome manual work required to convert raw machine log data into actionable information. Glassbeam Edge™ offers sophisticated IoT Analytics at the edge through a lightweight, yet powerful, platform that enables device manufacturers to perform mission critical activity in near-real-time without dealing with the costs or latency involved in sending data back to a central cloud.
Glassbeam Studio gives business and technical users immense data modelling power at their fingertips through the industry’s first ever data transformation and preparation tool for unstructured machine log data. Using Studio, a user can easily model and transform any kind of log format complexity through a friendly drag-and-drop interface. With this ground breaking functionality, the power of Glassbeam Studio is to revolutionize the IoT analytics industry by dramatically reducing the time it takes to design, implement and maintain an end to end IoT solution, by a factor of 100x.
Acting on the customer and partner feedback, we have built Glassbeam Studio and Edge Capabilities to alleviate two of the biggest pain points in the IoT industry,” said Puneet Pandit, Co-founder and CEO of Glassbeam. “Glassbeam is turning the IoT industry on its head with these new innovations. Now our platform has the most complete set of functionality for tackling the most daunting analytics challenges for the connected machine world and we are thrilled to make these available to the marketplace today.”
Glassbeam, as a long standing partner of the ThingWorx Ready partner program, will also be working closely with the ThingWorx Machine Learning platform to exploit the functionality of Glassbeam Studio and dramatically reduce the time to draw insights in machine learning projects. The ThingWorx platform helps automate the data discovery and predictive analytics process, speeding time to insights and reducing the dependency on expert resources normally required to create, operationalize, and integrate advanced or predictive analytics for key decision makers in the enterprise.
It is a well-known fact that machine learning models are only as good as the data that is used for training and on-going predictive scoring. Unfortunately, by some industry estimates, over 60% of the time in a typical machine learning project is spent in data preparation and transformation before any meaningful analysis can be performed. This is particularly true in machine learning projects with unstructured log data where data scientists’ precious time is spent in doing these mundane repetitive tasks as opposed to spending time on building valuable models and predictions. Glassbeam Studio is a revolutionary solution to this chronic problem.
Analytics and machine learning in the IoT world have a significant dependency on data transformation and preparation especially when dealing with unstructured machine log data,” said Ryan Caplan, President and GM of Analytics at PTC. “This problem gets more compounded when you have to combine unstructured log data with its varying complex formats with structured data sources to create richer data sets for deeper analysis. We believe Glassbeam has created a valuable footprint in this space and GB studio is another proof of their mission to simplify IoT analytics implementation life cycles.”
Additionally, Glassbeam is announcing the availability of edge computing capabilities through a lightweight version of its platform that ingests, parses and analyzes unstructured data in close proximity to the actual device. These capabilities eliminate the significant, often prohibitive, costs and latency involved in sending voluminous data back to centralized data centers. Glassbeam’s edge capabilities are particularly useful for high growth IoT areas like predictive maintenance in verticals such as smart grids, oil and gas, and power generation.
The promise of business IoT analytics is to transform and act on new machine information in real time,” said Jason Stamper, Analyst at 451 Research. “However, that has not been possible in the past due to lack of robust data transformation and analytics tools. With Glassbeam Studio, the ability for product manufacturers and service providers to transform complex machine log data into actionable information in minutes is going to have a major impact on the industry.”
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