- by Harinath Vicky, Prospector
- 10/30/2014 1:10:11 PM
- by ruehmkorf, Prospector
- by BritInBigD, Prospector
- 1/21/2013 8:45:31 AM
I was curious to know the source of the graphic that accompanies your post (and specifically the indicative growth rates shown for the different data categories). Is that data from IDC?
- by impactnow, Blogger
- 12/31/2012 6:56:50 PM
@Hospice I agree, but I don't know of any standard protocools because their is so much varaibaility with unstructured data depending on industry etc. Still a challenge to get standards.
- by Nnanci, Blogger
- 12/31/2012 8:50:05 AM
webmetricsguru, - One big challenge i see is analytics of sentiment oriented data even though the area has grown a great deal in the course of this year -- new apps and all. This kind of data at least for now may still need to be reviewed closer because its difficult to automate it in one given pattern without locking out new sentiments that are outside of that original set. However as intelligent systems learn this data, it will cut down what we have to look at even in sentiment analytics.
- by webmetricsguru, Blogger
- 12/30/2012 11:35:11 PM
If I understand you correctly, that's the bane of the PR / Marcom industry - that you can actually look at bunch of verbatim (maybe that's ok for 10-30) but what happens when you have thousands or more?
I think a discussion on just what cleaning data is and how to to best do it would be good for AllAnalytics.com personally. I'd like to see what we come up with, and I bet a lot of others would too.
- 12/30/2012 11:21:17 PM
"If we can find the essential information or pattern, we might not need to look at most of it"
I see. I suppose that those hand-written patterns can just be domain specific and will be difficult to generalize. I agree that extracting the most useful patterns might be enough in most cases, as it difficult to think of all possible patterns. One of drawback of such model is that human patterns are often low-recall, even if precision is high.
- 12/30/2012 11:05:50 PM
It is true that some of the points you mentioned are debatable - like "Distribute the data in the cloud". But they are valid points to take into account when dealing with unstructured data. To the question how to clean unstructured data? I think that it depends on the shape and the model that has been defined.
- by webmetricsguru, Blogger
- 12/30/2012 11:05:17 PM
What I meant is that currently, people usually end up needing to look at the data to understand it (because it is un structured information) and attempts to use software to understand it, in my opinion, won't work, at least not today. What you can do, I think, and maybe our friends here can confirm or argue this, is cut down on what we have to look at. If we can find the essential information or pattern, we might not need to look at most of it - and hopefully the software created can help surface that information, and maybe that's the best we can hope for (big data hype or not). At any rate, this is an interesting discussion and I don't have all the answers - but I am wondering just what they are.
- 12/30/2012 10:52:47 PM
"I define it as something a human needs to look at to fully process"
I still don't get it. Do you mean that there is the need for human intervention to figure out whether the data is unstructured or not? Won't that be time consuming and practically impossible for human to go through all the instances of the data due to it size? Maybe it is not what you mean?