We have a variable n which sets granularity.

level of granularity, would be 12,500 less than that.

So we lose a little bit of granularity of information.

Data, data, data...

Bing! That's data. Data, data, data.

Experiments show that it's best to stick with a granularity you once have achieved, because then you won't have to track back through all the levels of granularity you already have seen.

We simply keep on working with these new reduced, simplified inputs and a decreased granularity.

You don't necessarily know with granularity exactly what organisms are providing what flavors and what characteristics.

Say sorted data is data.

little data, old data, no data. So back in 1995,

Data

Data...

Data

Data

Data

Data

like DNA data or brain data.

Raw data now! Raw data now!

looking at wind data and solar data.

We define the length of the individual subset by simply dividing the length of the entire input by occurring granularity.

We could talk about government data, enterprise data is really important, there's scientific data, there's personal data, there's weather data, there's data about events, there's data about talks, and there's news and there's all kinds of stuff.

Data Viewer

(binary data)

raw data

? target data?

Merge data

Data Mode

Data mode

Data size

Data encoding

Data Section

Data Project

Text Data

Data DVD

Data CD

Data Disk

Preparing data

ISO9660 data

Writing data

Data Protection

Data Directory

Move Data

Check Data

Delete Data

Keep Data