Machine Data Analytics

Puneet Pandit, CEO and co-founder of Glassbeam, Inc.

The Internet of Things (IoT) is creating a new world of connected devices. Businesses generate immense data – in all formats. Because of this, the next frontier in IoT will be analytics. As the volume and variety of IoT-connected devices and machines grow dramatically, business users are demanding higher-velocity analytics on streaming data. In addition, users will continue to demand analytics on streaming data for proactive intelligence to create customer and business satisfaction – and ultimately tremendous value. The winners in analytics will be differentiated with specific platform capabilities to provide machine learning and real-time analytics.

At Glassbeam, we’re focused on bringing structure and meaning to data from any connected device, providing actionable intelligence around IoT. We recently announced the latest release of our core platform – Glassbeam SCALAR, a next generation cloud-based platform focused on predictive analytics. It’s designed to organize and analyze multi-structured data for powerful product and customer intelligence with detailed insights for today’s IoT devices and machines.

In addition, this new version of Glassbeam SCALAR is tightly integrated with Apache Spark™. These new capabilities and features strengthen Glassbeam offerings as it continues to maintain market leadership in ingesting, parsing and transforming complex machine data for some of the largest product manufacturers worldwide.

Integrating the Apache Spark engine, Glassbeam is able to deliver a fast, in-memory distributed data processing framework for large-scale data. This allows the platform to be 100x faster than the traditional Hadoop MapReduce architectures. Additionally, Glassbeam is adding new machine learning and predictive analytics capabilities to the core platform.

Glassbeam goes beyond analytics that narrowly focus on index, search and analysis of simple data formats from IT assets locked away in data centers. Built for the Internet of Complex Things, the platform processes large amounts of data with extreme speed, employing advanced machine learning algorithms and real-time analytics. This means Glassbeam customers can crunch years of data in a very short time to produce rich intelligence that helps avoid problems and totally optimizes business operations.

Glassbeam’s SCALAR was designed for complex, multi-structured machine data and the new realities of business IoT. With these new capabilities, Glassbeam is now uniquely positioned as the only company to provide rich machine learning algorithms and real-time processing for complex machine data.

For example, use cases will allow product manufacturers to become more proactive by preventing part failures, or predict which machines or parts are susceptible to higher failures rates in future. As a result, manufacturers can prescribe solutions to problems before they happen in the field.

With a high-speed platform with distributed data and compute architecture, these levels of advanced analytics will translate into millions of dollars in cost savings through improved support and field service operations. By the same token, similar analytics will allow manufacturers to better understand customer and product behavior that will create new streams of services and up-sell revenues.

The new version of Glassbeam SCALAR provides performance and scalability and also advanced and real-time analytics. The patent-pending, cloud-based technology enables customers to reduce costs, increase revenues, accelerate product time to market, and improve customer satisfaction and retention.

This is an exciting time for the industry as a whole. As more and more connected devices continue to collect data, more business users will reap the value, ultimately creating both customer and business satisfaction.