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Wayne Eckerson

Welcome to Wayne's World, my blog that illuminates the latest thinking about how to deliver insights from business data and celebrates out-of-the-box thinkers and doers in the business intelligence (BI), performance management and data warehousing (DW) fields. Tune in here if you want to keep abreast of the latest trends, techniques, and technologies in this dynamic industry.

About the author >

Wayne has been a thought leader in the business intelligence field since the early 1990s. He has conducted numerous research studies and is a noted speaker, blogger, and consultant. He is the author of two widely read books: Performance Dashboards: Measuring, Monitoring, and Managing Your Business (2005, 2010) and The Secrets of Analytical Leaders: Insights from Information Insiders (2012).

Wayne is founder and principal consultant at Eckerson Group,a research and consulting company focused on business intelligence, analytics and big data.

Stream processing has idled on the backwaters of the analytic market for years. But with the advent of Hadoop and new open source streaming tools, such as Storm, Spark, and Kafka, many companies are taking a closer look. And many stream processing tools are finally finding a home with the Internet of Things, in which consumer and commercial devices--from smartphones and household appliances to automobiles, utility meters, and medical equipment--emit millions of events per second and require specialized analytical systems to process them in real time.

Stream processing platforms, like SQLstream, provide both the horsepower and smarts to filter, aggregate, group, compare, and analyze large volumes of data in flight as well as visualize the results in real time. Telecommunications companies use SQLstream to monitor network performance, track service usage, and detect fraud in real time; oil and gas producers use it to monitor operations of drilling rigs, digital wells, and intelligent oil fields; and transportation companies use it to monitor traffic congestion, among many other things.

Compared to Storm and Spark, SQLstream is a complete enterprise platform for streaming analytics that can be deployed quickly without a large development effort. Whereas the open source projects are free to download, they require a lot of development talent and time to make work, especially in high-volume environments. Moreover, SQLstream, which gets its name because it uses continuous SQL to generate analytics, runs more efficiently, requiring many fewer servers and less overall expenditures.

As devices become more intelligent with the addition of sensors, product companies will need to invest in stream processing systems to make sense of the deluge of data. SQLstreams is well positioned to capitalize on the emerging Internet of Things.

For more information, see www.sqlstream.com


Posted September 16, 2014 11:22 AM
Permalink | 2 Comments |

2 Comments

Wayne, good perspective on Event Stream Processing and The Future of SQL. Of course some of the examples you give such as Intelligent Oil Fields is one which is being classified within the Internet of Things and in particular, the machine to machine environment. What I believe would also be helpful is if we round out what IoT means in terms of SMAC. While SMAC 1.0 is Social, Mobile, Analytics and Cloud. SMAC 2.0 is Sensors Machines, Analytics and Connected Systems and Societies. Both can stand alone but in reality both will be blended in a bigger service and digital experience professionally or socially. Food for Thought and Would Love to Discuss More. Regards Tony.

Hi Wayne

I echo the compliments above, but just wanted to bring your attention to the integration between Streambase (which TIBCO purchased around 15 months ago) and the Spotfire analytics platform.

Early adopters of the dual solution are prevalent in the digital oilfield (eg monitoring ESP's and drilling) and industrial equipment such as turbines.

A twist we provide is the incorporation of predictive models predicting failure times (or other adverse conditions). As these are also monitored over time they become self-improving.

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