Who we are

We deliver analytical insights, leverage machine complex data, and empower end-users with business intelligence.

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.

IOT for farming

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.

Edge analytics in glassbeam

So you heard me TALK ABOUT edge computing. Now lets look at edge analytics. In other words, dynamically created business rules implemented at run time? Hmmm, great idea, but difficult to implement. Even more difficult if you further simplify the generation of such rules through an intuitive drag and drop UI. Analytics is another name for early action and Rules are key to making that happen. Rules allow us to:

Glassbeam edge computing – a primer

As the Internet of Things inevitable starts coming into it’s own, the origin of data has evolved from people to machines to “things”. Technologies emerged from leaders like Google and Facebook to enable analyzing tons of data in massive data farms deployed in the cloud. All that is well and good, but the approach itself needed moving this “ton” of data to a central location, partition it across large number of nodes so that analysis could be parallelized. Imagine, Netflix has over 1,000 nodes in their cluster. Hmmmm, doable, but at some point the laws of physics start to interfere.

Glassbeam studio architecture

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

Introducing glassbeam studio

I am delighted to announce the release of Glassbeam Studio – the industry’s first Data Transformation and Preparation tool for complex machine data.

According to Gartner, by 2018, data discovery and data management evolution will drive most organizations to augment centralized architectures with decentralized approaches. Most business users and analysts will have access to self-service tools to prepare data for analysis.

Pages