PREDICTIVE ANALYTICS

Glassbeam Analytics Changes the Game for Clinical Engineering and Imaging Equipment Service Teams

Rick Gaylord
Mar 16, 2018

In my role as the Healthcare Solutions Specialist for Glassbeam I've had the opportunity to meet with a wide range of Glassbeam customers and partners. I've spoken to members of the C-Suite, Directors of Clinical Engineering, and Field Service Engineers/Imaging Service Engineers (FSEs/ISEs) on the frontlines of imaging system service.

How much does medical equipment downtime cost hospitals?

Puneet Pandit
Aug 31, 2017

The increasing demand for better diagnostics is putting pressure on hospitals to invest in high-end medical imaging equipment such as ultrasound and X-Ray devices, computerized tomography (CT) scanners, magnetic resonance imaging (MRI) scanners, and positron emission tomography (PET) scanners. These machines can range from several hundred thousand to a few million dollars each.

Glassbeam for Glassbeam (Part 3) – Making our Support Team Super Heroes!

Pramod Sridharamurthy
Jul 31, 2017

In the second post of this series, I have listed the high level use cases of Glassbeam for Glassbeam across our internal teams: Technical Support, Sales, Engineering, and Product Management. In the next 4 posts, I will dive deep into the use cases for each of the above teams and talk about the value Glassbeam for Glassbeam as a data-driven decision making solution, brings to each team.

PTC and Glassbeam to Showcase Industry Leadership in Internet of Things Analytics

Vijay Vasudevan
Sep 15, 2016

We are working with our partner PTC to produce a series of thought-leadership materials aimed at helping developers, business managers, Internet of Things enthusiasts get started on the ThingWorx Analytics Internet of Things (IoT) platform.

Here’s the announcement from PTC on the upcoming thought leadership meetups: https://www.thingworx.com/about/news/ptc-thingworx-partners-showcase-industry-leadership-iot-analytics/

On to liveworx 2016

DEVANG MEHTA
May 06, 2016

We’re just about wrapping up a wonderful week at TSW in San Diego where we met with tons of Support practitioners and discussed with them numerous ways to help them transform their Support organizations into Profit Centers. Now, we’re getting prepped for LIVEWORX – traditionally the biggest Conference for us every year

Actionable feedback right through edge computing

ASHOK AGARWAL
Apr 07, 2016

Continuing our discussion on Edge Computing and Analytics ….. Remember WE SAID that a key benefit of Edge was Local Decision Making. Typically, that will preclude access to the install base data. However, there is a wealth of information which can be gleaned from the install base data (such as machine learning output). It seems a shame to not be able to utilize that on the edge.

Glassbeam edge computing – a primer

ASHOK AGARWAL
Feb 22, 2016

As the Internet of Things inevitable starts coming into it’s own, the origin of data has evolved from people to machines to “things”. Technologies emerged from leaders like Google and Facebook to enable analyzing tons of data in massive data farms deployed in the cloud. All that is well and good, but the approach itself needed moving this “ton” of data to a central location, partition it across large number of nodes so that analysis could be parallelized. Imagine, Netflix has over 1,000 nodes in their cluster. Hmmmm, doable, but at some point the laws of physics start to interfere.

Glassbeam studio architecture

SURAJ ATREYA
Feb 17, 2016

GLASSBEAM STUDIO is a one of a kind software which helps in data transformation and preparation, visualizing data, deployment and much more. The Glassbeam Studio technology is modeled on a client-server architecture with functionalities balanced neatly between the client and the server. This software is architected to offer an infinitely scalable, seamlessly, and functionally compelling way to transform even the most complex machine data into valuable business insights.

Metadata extraction

Semiotic parsing language – the language for machine data analytics

PRAMOD SRIDHARAMURTHY
Jan 13, 2016

The Internet of Things (IoT), an ever-growing number of connected devices, generates vast amounts of data, called “Machine Data”, complex in variety, volume and velocity. Machine data is information about the device, like its configuration, status, performance, usage and more. Manufacturers across data-intensive industries – such as storage, wireless, networking and medical devices – are struggling to make sense of all this data. Analyzing machine data can help organizations with reactive diagnostic activity, predictive problem identification, and business intelligence.

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