BIG DATA ANALYTICS

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.

Congratulations to our authors at glassbeam!

PRAMOD SRIDHARAMURTHY
Jan 07, 2016

One of the best things for us at Glassbeam has always been the team! We have some of the smartest engineers with each one an expert in their domain. 2016 was a great start for three engineers here as they became first time authors on topics that are core to what we do at GLASSBEAM. The important part is that they wrote these books without impacting work schedules, which shows the passion and commitment they have for their craft.

Build versus buy – an empirical approach (part 1)

DEVANG MEHTA
Nov 24, 2015

In this two-part Blog post, we will examine the pros and cons or building an in-house IOT ANALYTICS SOLUTION versus licensing a solution from a leading industry player like Glassbeam…

IOT analytics fuel the brick and mortar retail revolution

DEVANG MEHTA
Nov 16, 2015

Brick and mortar retailers are in a life struggle with online marketplaces. Brick and mortar retailers operate with the added expense of maintaining a physical facility, keeping inventory on hand and hiring service staff to support customers.

Savvy retailers are continuously seeking out new information about their customers; how they browse the store, what they buy, when they buy it, and which marketing “levers” are responsible for those sales. Some are even turning to technologies as elaborate as creating virtual store shelves and studying shoppers’ eye movements.

Converged infrastructure, here we come!

DEVANG MEHTA
Sep 01, 2015

We always feel elated when we enter a new vertical and win a couple of customers in the space. The joy and excitement is amplified when it’s a white-hot vertical by itself – in this case the Converged and Hyperconverged (simply “Converged” for this post) Infrastructure space.

New analyst coverage reflecting exciting developments

DEVANG MEHTA
Aug 20, 2015

It’s a busy summer at Glassbeam – we’re entering new verticals and also rolling out some game-changing product features. We constantly talk to industry analysts to keep them abreast of key developments at Glassbeam, and as a result of these conversations a couple of important Analyst coverage reports have been published in recent times.

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.

IOT analytics a critical success factor in today’s "big storage"

DEVANG MEHTA
Jul 08, 2015

The pervasiveness of big data has led to an equally significant expansion of what can be called “big storage.” Whether you’re a cloud service provider or an enterprise, managing that big data requires highly complex and sophisticated storage systems. Failure of these systems is not an option.

Storage system providers have turned to IoT analytics both to help ensure optimal performance and to gain a deeper understanding of how customers are using their solutions.

The era of qoe on steroids

VIJAY VASUDEVAN
Jun 17, 2015

Glassbeam has built a predictive analytics app built for telecommunications operators and providers. This app aims to leverage benefits from our machine learning models. It is designed to automatically turn raw data from networking equipment into actionable operational intelligence. Whether it is solving a support escalation or looking for opportunities to price the services effectively, this app has it. In case you missed it, here is a recent PRESS RELEASE on the QoE app launch.

What’s in the Sauce: The True Picture of the QoE Solution?

Connected medical devices and iot analytics combine to save lives

DEVANG MEHTA
Jun 12, 2015

Among the most dynamic market segments where IoT analytics has the potential to grow rapidly is medical devices. Market research firm FREEDONIA GROUP notes that 2.5 million people rely on these devices today and predicts the market will grow 7.7 percent in 2015. More than 300,000 Americans receive these devices each year.

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