So what you're seeing is you have 5% or more sample of the picture so you have a

keyhole of data into this this picture. Many of us have been looking at data

through this data keyhole. It's very hard to understand what the whole population

looks like the whole big picture and that's really what big data is about. So

when I show you the whole picture you immediately say of course this is a

Brooklyn Bridge. Now you have the whole picture. Okay so the point here is that

big data allows you to look at the whole picture not a statistical sample and of

course that's the whole point of the talk is with this you have the entire

picture, so some of you are probably thinking well Mike if we're doing this

analysis do we have to go through every single report and dig this information

out? Some of you also might be thinking I mean it would really be nice if we had

all this data in one little database where we could use it freely. Well that's

where I'm going folks. That's the good news.

About a month ago we published the financial statement and notes data sets.

This is freely available on the SEC website and what it includes is back to

2009 all of the structured data for all of the company financial statements. So

in the past we've been publishing financial statement data sets which was

just the data from the actual financial statements this includes the financial

statements and all of the note disclosures, both numeric and narrative

disclosures in the notes. Okay that's important because that's where a lot of

the details are that the devil is looking for, so if you're interested this

is out there. If you're doing analysis on financial statements the other thing I

would point out about this data set is that it's of every single public company

filing 10k and 10-q financial statements it's not just the top three fouls on to

the top 2000. it's literally all financial statement filers for the

period from '09 through today and we update it quarterly. There's no licensing

restrictions. It's freely available for you to do research on.

Thank you very much.