Taneja Group | SCALAR
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Trusted Business Advisors, Expert Technology Analysts

Items Tagged: SCALAR

Profiles/Reports

Glassbeam SCALAR: Making Sense of the Internet of Things

In this new era of big data, sensors can be included in almost everything made. This “Internet Of Things” generates mountains of new data with exciting potential to be turned into invaluable information. As a vendor, if you make a product or solution that when deployed by your customers produces data about its ongoing status, condition, activity, usage, location, or practically any other useful information, you can now potentially derive deep intelligence that can be used to improve your products and services, better satisfy your customers, improve your margins, and grow market share.

For example, such information about a given customer’s usage of your product and its current operating condition, combined with knowledge gleaned from all of your customers’ experiences, enables you to be predictive about possible issues and proactive about addressing them. Not only do you come to know more about a customer’s implementation of your solution than the customer himself, but you can now make decisions about new features and capabilities based on hard data.

The key to gaining value from this “Internet Of Things” is the ability to make sense out of the kind of big data that it generates. One set of current solutions addresses data about internal IT operations including “logfile” analysis tools like Splunk and VMware Log Insight. These are designed for a technical user focused on recent time series and event data to improve tactical problem “time-to-resolution”. However, the big data derived from customer implementations is generally multi-structured across streams of whole “bundles” of complexly related files that can easily grow to PB’s over time. Business user/analysts are not necessarily IT-skilled (e.g. marketing, support, sales…) and the resulting analysis to be useful must at the same time be more sophisticated and be capable of handling dynamic changes to incoming data formats.

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Publish date: 10/21/13
Profiles/Reports

Converged IT Infrastructure's Place in the Internet of Things

All of the trends leading towards the world-wide Internet of Things (IoT) – ubiquitous, embedded computing, mobile, organically distributed nodes, and far-flung networks tying them together - are also coming in full force into the IT data center. These solutions are taking the form of converged and hyperconverged modules of IT infrastructure. Organizations adopting such solutions gain from a simpler building-block way to architect and deploy IT, and forward-thinking vendors now have a unique opportunity to profit from subscription services that while delivering superior customer insight and support, also help build a trusted advisor relationship that promises an ongoing “win-win” scenario for both the client and the vendor.

There are many direct (e.g. revenue impacting) and indirect (e.g. customer satisfaction) benefits we mention in this report, but the key enabler to this opportunity is in establishing an IoT scale data analysis capability. Specifically, by approaching converged and hyperconverged solutions as an IoT “appliance”, and harvesting low-level component data on utilization, health, configuration, performance, availability, faults, and other end point metrics across the full worldwide customer base deployment of appliances, an IoT vendor can then analyze the resulting stream of data with great profit for both the vendor and each individual client. Top-notch analytics can feed support, drive product management, assure sales/account control, inform marketing, and even provide a revenue opportunity directly (e.g. offering a gold level of service to the end customer). 

An IoT data stream from a large pool of appliances is almost literally the definition of “big data” – non-stop machine data at large scale with tremendous variety (even within a single converged solution stack) – and operating and maintaining such a big data solution requires a significant amount of data wrangling, data science and ongoing maintenance to stay current. Unfortunately this means IT vendors looking to position IoT oriented solutions may have to invest a large amount of cash, staff and resources into building out and supporting such analytics. For many vendors, especially those with a varied or complex convergence solution portfolio or established as a channel partner building them from third-party reference architectures, these big data costs can be prohibitive. However, failing to provide these services may result in large friction selling and supporting converged solutions to clients now expecting to manage IT infrastructure as appliances.

In this report, we’ll look at the convergence and hyperconvergence appliance trend, and the increasing customer expectations for such solutions. In particular we’ll see how IT appliances in the market need to be treated as complete, commoditized products as ubiquitous and with the same end user expectations as emerging household IoT solutions. In this context, we’ll look at Glassbeam’s unique B2B SaaS SCALAR that converged and hyperconverged IT appliance vendors can immediately adopt to provide an IoT machine data analytic solution. We’ll see how Glassbeam can help differentiate amongst competing solutions, build a trusted client relationship, better manage and support clients, and even provide additional direct revenue opportunities.

Publish date: 08/18/15
news

Glassbeam Enters Converged and Hyper Converged Infrastructure Market

Company's Ground Breaking Machine Data Analytics Solution Already in Production With Two Leading Product Vendors

  • Premiered: 08/31/15
  • Author: Taneja Group
  • Published: MarketWatch
Topic(s): TBA Glassbeam TBA converged TBA Converged Infrastructure TBA hyperconverged TBA hyperconvergence TBA hyper convergence TBA machine data TBA analytics TBA Big Data TBA Internet of Things TBA IoT TBA data analytics TBA Saas TBA SCALAR TBA Cloud