Medical Device Usability is a Dire Need, Not a Nice-to-Have Option

The connected medical equipment is here and the possibilities of a fresher, richer future are staggering. Imagine CAT scanners talking back to technicians, initiating reports on its profitability, or does a self-diagnosis and tells product management they ought to replace it. These possibilities are not too far into the future but we’re almost there.

7 Must Have Items on Your Checklist Before You Consider Machine Data Analysis

These are the 7 key factors that highlight whether performing machine data analysis realizes credible value for you.

1. Prepare the raw data —

Most of machine data are in the form of logs. Industrial machines are constantly producing valuable operational data (call-home data) on configuration, performance, usage, and other important parameters that define the very life of the device in the field.

Ingesting call-home data — learnings from the trenches

At Glassbeam, we deal with terabytes of data daily. Our SCALAR platform ingests and parses many files in real time. (The files arrive asynchronously and fast!) These files are then picked up for parsing in the order in which they arrive. For such a demanding requirement, we had to design a system which should not only be concurrent and asynchronous but also scalable.

Why phone-home makes strategic sense?

I have come across many sales situations where customers are unsure or wary of asking their customers to send regular feeds of the machine-generated data (logs). This feature is known as phone-home or call-home. The fact is that all high technology devices, systems and networks are constantly generating all kinds of log data (syslogs, configs, stats, static etc). This is now called the Internet of Things (IoT) phenomenon.

Glassbeam @ strata

We had a great launch at Strata. Many people stopped by and had wonderful things to say about our new product – Glassbeam Search a unified search and log management solution. We got several good pieces of advice and feedback as well and many thanks to all of you.
As we continue building this out we find most companies needing the following

Analyzing logs and more. A big data reference architecture

Analyzing logs and more- a Big Data reference architecture for processing product logs and other data.

Big data and log files

Splunk’s great success in providing the tools for a sysadmin to delve into previously inaccessible log files has opened up the market for deeper analysis on data in log files.

ABCS of log file analytics

A. Aggregate data from all log files – All log files are not the same – Most people think of sys logs when they think of log files – no thats not all. Logs from product and software companies are bundles containing many files each of different types and formats. Some are time series data of events but others can be stats, session information, usage metrics, configuration etc.

Big data and dsl ( domain specific language )

DOMAIN SPECIFIC LANGUAGES have been around for a long time – a great example of a DSL is SQL for RDBMS. A DSL is differentiated from a general-purpose language such as C, Java or Python since a DSL is geared towards a specific domain.

Moneyball for sales and service

With the buzz around Big-Data it is important to keep in mind what can be done with the data. For those of us who have read or watched Money Ball it is apparent that you can use insights derived from data and combine that with your intuition to make better decisions.

Glassbeam gives you the tools to make such decisions in your business, based on unfiltered machine data.

Glassbeam and support teams

We’re in the midst of finalizing a case study featuring how one of our customers used Glassbeam to make it’s support organization more efficient. Will be sure to update you when we launch the case study, but can share some key findings,

One of the greatest benefits of using Glassbeam was the usage of threshold events and automatically opening cases in CRM systems (hitherto done by L1 support personnel). This resulted in substantial cost savings.