Simoudis mentions that today what is generally referred to by “big data” means data that is large in size, semi-structured or unstructured in form, and real-time or near real-time in the way it is generated and consumed. This melds well with another description of the two different types of big data – “fast” big data that is real-time and “slow” big data that is generally needed for analysis and hypothesis testing.
Simoudis is Managing Director at Trident Capital, focusing on investments in Internet and software businesses, and here’s what he had to say in the Enterprise Irregulars post about why he believes IBM’s Watson technology is important:
1. First, it uses a question and answer interaction which business users find more natural as it enables them to incrementally improve their understanding of a problem.
2. Second, it effectively combines structured with unstructured data some of which is curated, such as published articles of special or general interest, while other is dynamically collected from the open internet.
3. Third, Watson’s data analysis speed, that is the result of its underlying architecture, makes the system suitable for several application areas, particularly those where data remains useful for a short period such as medical analysis, financial analysis, and consumer sentiment analysis.
4. And finally, Watson’s concurrent use of many analysis and prediction techniques, not only provides a unique approach to machine learning and fact-prediction, but more importantly it enables the analytic application to explore more alternatives to a possible solution, thus increasing the probability of successfully addressing a problem.
I do believe that this is where analytics technology development is heading – we’ve taken note of IBM’s Watson technology some time back. You can read more about Simoudis’ thoughts and his IOD talk here…
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