MACHINE DATA

Redefining Art of Analyzing Medical Machine Logs: Glassbeam Q2 Milestones and Momentum

Puneet Pandit
Jul 17, 2018

Most would consider analytics a science. The Glassbeam team considers analytics an art of combining impermeable truth from machine logs with deep healthcare domain expertise.  As we expand our penetration of the healthcare market after spending years in the data center world, where the gold standard for machine uptime was 99.999 percent, we have recognized a huge opportunity since the acceptable machine uptime for medical equipment ranged from 90 to 97 percent.

Data Doesn’t Lie: 5 Ways Hospitals Can Use Machine Log Data

Pawan Jheeta
Jul 04, 2018

Maximizing uptime of diagnostic equipment is vital to both patients and healthcare organizations. As medical imaging equipment becomes more sophisticated and the need for healthcare organizations to improve their availability becomes more acute, so does the value of machine log data and advanced analytics. Here, we’ve listed several important ways that hospitals can use machine log data and predictive/prescriptive analytics to optimize operational efficiency and revenues.

Semiotic Parsing Language (SPL) - Breakthrough DSL for IIoT Analytics - Part Two

Ashok Agarwal
Jun 13, 2018

In this section we will investigate how Glassbeam’s DSL called SPL (Semiotic Parsing Language) helps in parsing multi-structured machine logs.

SPL Terminology:

Namespace:

SPL allows a log file to be treated as a hierarchical document consisting of multiple segments (or sections). Each hierarchical segment is called namespace. This allows for zeroing in on the exact section to parse specific elements from, thus localizing the scope of extracts.

New FDA Report Highlights the Importance of Servicing Medical Devices

Puneet Pandit
Jun 05, 2018

This month, the FDA issued a report that focused on the quality, safety, and effectiveness of servicing of medical devices.

Semiotic Parsing Language (SPL) - Breakthrough DSL for IIoT Analytics - Part One of Two

Ashok Agarwal
May 30, 2018

Introduction

Glassbeam’s business revolves around providing business intelligence on machine data. Intelligence comes from structured data. Machine data is not always structured. So, there is a gap between what is needed and what is produced. As Glassbeam’s head of engineering, I am going to write a two series blog about how Glassbeam bridges this gap.

If It’s Not Broken You Can Still Fix It: ISOs See Value of Predictive Analytics

David Sawatzke
May 24, 2018

Capital expenditures for healthcare equipment totaled more than $350 billion in 2016, according to Harbor Research. Healthcare organizations and Independent Service Organizations (ISOs) are now turning to AI and machine learning to predict and prevent equipment failures and reduce operational costs.

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/

Elastically adding and removing nodes using akka cluster

SURAJ ATREYA
Aug 07, 2015

This post explores a pull-based master/worker architecture – one that is suitable for anyone who is looking to elastically provision nodes when the load is higher than normal and under-provision when the load is below normal. In this post, the master accepts RSS links from frontend which can be a user submitting links and worker accept one RSS link and extract information such as article’s published date, title and a brief description. All this information is indexed into ELASTICSEARCH.

Virtues of call-home data

DEVANG MEHTA
Sep 02, 2014

Call-home data is one of the often-used buzzwords in the IOT world; yet the nuances and complexities of instrumenting devices and sending back data in a secure and timely manner are often under under-appreciated. This is a bit mystifying, since following best practices in this area can greatly move a company up in its ability to provide product intelligence, health check services, and support automation to end-customers; indeed for IOT-savvy companies the evolution of call-home practices is often in lockstep with the company’s evolution as a whole.

Come join our webinar on machine data security

DEVANG MEHTA
Jul 28, 2014

At times, we encounter apprehension from customers, prospects, and partners about how secure end-customer data is on the cloud. To address, these concerns we’re hosting a Webinar with our Infrastructure-as-a-service partner, Dimension Data, next week. And we’ve lined up a star panel including our VP of Engineering, Ashok Agarwal and David McKenzie, Sr. Director, Solutions Architects at Dimension Data for you.

 

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