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Enterprise-class real-time stream analytics for Big Data

Since the beginning of the information age, enterprises have relied on processing data to gain insights and make business decisions. In the past decade, significant advances in technology have fostered the dramatic increase of data complexity in volume, variety, and velocity – the ‘three V’s’ of Big Data.

For example, 9 billion devices are connected to the Internet today– from laptop and desktop computers to tablets, smartphones, even home entertainment systems and thermostats. By 2020, that number is expected to be 50 billion. With such a dramatic increase in connected devices, a significant increase in data generation and processing will naturally follow.

This massive increase in data workloads has led to advances in new parallel processing frameworks that use distributed computing on distributed data sets, such as MapReduce on Hadoop. Hadoop, in turn, has seen rapid adoption because it is much cheaper than traditional mainframe proprietary storage solutions.

via Enterprise-class real-time stream analytics for Big Data – Datanami.

Go Big with Data

My current focus is directing and managing strategic and operational aspects of Pragmatic Works, a data services organization focused on democratizing analytics and data related technologies. I built the organization from the ground up (with my co-founders) to include industry leading processes, attract and retain top industry resources and execute powerhouse partnerships with firms like Microsoft and HP to deliver the highest quality solutions in the most innovative ways.


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