Ventana Research
JAN 25, 2012 3:38pm ET

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Big Data is More Than Hadoop


We recently published the results of our benchmark research on Big Data to complement the previously published benchmark research on Hadoop and Information Management. Ventana Research undertook this research to acquire real-world information about levels of maturity, trends and best practices in organizations’ use of large-scale data management systems now commonly called Big Data. The results are illuminating.

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Comments (2)
David, great insight on these Big Data trends. I'd like to point out HPCC Systems is a mature platform which presents numerous benefits over Hadoop and other alternatives, including a consistent and homogeneous architecture, and end to end solution including data workflows and data delivery (through the Thor and Roxie components), and a high level data oriented Domain Specific Language (DSL) called ECL, which enables the analysts to quickly and effectively define complex data ETL (Extraction, Transformation, Loading), Linking and Delivery processes. The HPCC Systems platform is quickly evolving to include ready to use and completely parallel implementations of solutions in different areas, such as Machine Learning, Statistical analysis and Document processing. For a more complete picture, visit
Posted by HAANA M | Friday, January 27 2012 at 7:53PM ET
Hello David -

Thanks for sharing the research of your recent study. Your thoughts are definitely in line with the advice that we are providing our clients. I especially appreciate your comment that there is no technological silver bullet, which you elaborate with a discussion about people and process. In addition, we feel there is not a "one size fits all" approach for the design of the technical infrastructure. Although we now have technologies that allow organizations to process all of the data, with an abundance of models and variables with high performance computing technologies such as in-memory, in-DB and grid, we also see a real need for identifying relevant information up-front in the process. This includes leveraging analytics on the front end of the process - so instead of always landing the data, you use analytics based on organization context to determine relevance, an approach that we refer to as "stream it, score it, store it".

On the Hadoop side, it's important for an enterprise to understand the implications of big data and how the new tools work before embarking on a big-data initiative. Keith Collins, our CTO, noted that "Those who are just standing up Hadoop as is, with no management framework, writing directly to it ... there's going to be some real disillusionment there. The data issues come after the question." He goes on to say that enterprises have to know what they want to find out from their data and then deal with how to get that out of their data.

We are blogging extensively on the role of Big Data Analytics and Hadoop, including a post which you can find here -


Mark Troester IT/CIO Thought Leader & Strategist SAS Twitter @mtroester

Posted by Mark T | Monday, January 30 2012 at 10:56PM ET
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