BIG DATA ANALYTICS

Smarter cities through iot analytics

DEVANG MEHTA
Mar 14, 2016

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.

IOT for farming

DEVANG MEHTA
Feb 29, 2016

When you think of life on the farm, a life of waking up before the rooster crows, then heading out to the fields for the day to seed, plow, fertilize and reap in the hot sun before going home for the night and starting over the next day usually come to mind.

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.

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.

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