Blogs

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.

Market validation in one wonderful iot landscape

Matt Turck at FirstMark recently wrote a wonderful post that outlined the CURRENT IOT LANDSCAPE (Glassbeam mentioned under Analytics) and the reasons for the somewhat slow growth of the marketplace despite all the surrounding hype.

On to liveworx 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

IIOT trends to be aware of

IIoT promises to transform the industrial landscape. Customers expect the industrial product usage experience to match the retail, such as the Apple iPhone or Amazon shopping. So, when customers engage with machines, they expect equally intuitive and seamless experiences.

Tis the season of conferences

Glassbeam is gearing up for Conference season – we are going to be attending two major events in Q2.

Partnering with tsia to transform support organizations

I must admit – the impetus for this post is squarely ANOTHER POST written by Judith Platz at TSIA.

Actionable feedback right through edge computing

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.

Brookings weighs in on bright prospects for iot

This morning, I read a fascinating compilation of thoughts on IoT in the Brookings Institution’s TECHTANK newsletter. What caught my eye first was the title, “Alternate Perspectives on Internet of Things.” The article is a series of brief opinions by six Brookings fellows.

Chosing an edge computing platform

Choosing an Edge Computing Platform

Does 25ms sound unreasonable to process Terabytes of data? Well it is in today’s IoT world – to collect gigantic amounts of data, process and analyze it, and generate snappy dashboards in just 25ms.

Leaders across industries are emphasizing that data absolutely has no value if it cannot be processed and transferred to a decision maker quickly enough for him or her to act quickly enough. Today, it’s impossible to accept even a minute’s delay.

Edge computing is propelling those huge expectations. And it ought to be.

Smarter cities through iot analytics

For the first time in history, MORE PEOPLE LIVE WITHIN CITIES than outside them. This huge influx of people means that cities have to be able to find ways to quickly provide services to larger numbers of people, rapidly uncover and analyze pain points in providing these services, and plan ahead to accommodate the continuing migration. In particular, more people translates to more cars on the road.

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