Is it vital to capture every stream of data in your organization to create truly continuous intelligence?

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CEO in Services (non-Government), Self-employed
I actually was thinking about, why is there not a set of component ware to help that stream become available, whether it's via NLP, via voice, via some other mechanism. There has to be a way to do it because there's a lot of researchers out there. You'll never be able to give me the insight that I need as a consumer, an operator, a CIO, or even somebody on a shop floor if you can't capture every stream of consciousness that is available through a device. Voice is now becoming bigger and bigger.
CTO, 11 - 50 employees
I think that's key to the idea of continuous intelligence.  The problem is fusing multiple real-time streams of data from different things: your sentiment, your location, a whole bunch of things, all of which are relevant to something I care about in my business. And so the problem is really the ability to rapidly and in real-time fuse these disparate data sources, come up with a way to reason across multiple things, multiple sources of information, find correlations, predict outcomes, whatever it happens to be, and then inform people so they can make the right decision or inform businesses so their apps can do the right thing. That's the hot piece. And so that's my definition of continuous intelligence.
CEO in Software, 11 - 50 employees
I don't know that I have a good definition. It is very difficult when talking to folks that have different views and different strategies for data collection to represent a single answer for how data will be collected or benefited from at the Edge. I'm not an expert on data by any stretch, but what I do know is that every data collection opportunity has different variables and reasons behind the collection and those reasons and variables determine how you can derive value from the data. For example, if you're doing something that is effectively building value on top of an original bit of information like you're attempting to find the next digit for Pi, then every bit of data you found previous to the last digit is immaterial, all you care about is finding the next piece of data that creates the next number in the series of numbers for Pi.

On the other hand, if you're looking for all of the different variables in the universe that have an impact on whether or not your sun will explode, then there's really not anything you can throw away, and you may not be able to throw it away historically, you may not be able to throw it away from a vector standpoint, you may have to keep all of it. The problem for us with data is that those two things are at both extremes of the data collection and analysis. And they're impacted by things like local law, long-term compliance and retention requirements, how fast you need to be able to get access to the value that's in them, and how often you need to get access to that value.
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CTO, 11 - 50 employees

Mark, one of the things I worry about though, is that individual data stream owners are often told to keep everything because you never know when it might be useful. In fact, in general, it isn't. Once it's sitting in hardware somewhere, it isn't useful and maybe goes back in time.

CEO in Software, 11 - 50 employees

Absolutely, you hear that every single day.

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