And, as Neural Dude has explained on this blog, the next generation of Big Data Analytics addresses the "gap" that exists between sensor or raw data and actionable information. At Neural ID, we've delivered solutions to John Deere, GM and NASA that address the subjective nature of unstructured data. Our Learn-Recognize-Act ® framework is an example of a pattern based strategy for unstructured data. And the "gap" in this context is making sense of data created by operational processes or consumer behavioral data in order to create business value. As this operational data and content grows exponentially, companies that can make sense of this data to take intelligent action will be competitive leaders.
Gartner VP and Distinguished Analyst Yvonne Genovese explains the importance of applying a Pattern-Based Strategy (PBS) approach to seek, model and adapt to patterns contained in big data. According to Genovese, this is the "ability to seek patterns, model their impact on the enterprise, and to adapt the enterprise pursuant to the needs of the pattern." It involves using data in real-time to ask what is happening right now, and what is likely to happen in the future.
In this presentation, Genovese explains how a Pattern-Based Strategy provides an approach to proactively Seek, Model, and Adapt to patterns that may have a positive or negative impact on your strategy or operations across many sources of current and evolving information.
Interestingly, our Learn-Recognize-Act ® framework parallels the Gartner approach. For those of you who have been following our progress at Neural ID, you know that we are developing industry-specific applications using our pattern seeking technology driven not by the "needs of the pattern" but rather what we call "intelligent value creation."
Our solutions are gaining worldwide acceptance as retail, health-care, manufacturing and other application developers can build their pattern recognition applications and offerings using Neural ID's CURE technology.
The future, as we mentioned in our previous blog post, is already here!