I recently came along this great cheat sheet explaining SQL joins. Doe’s not need nay further explanation, though…
Every week, there are many things I stumble upon worth blogging about. Unfortunately, there is either too much to at that time, just too little to say about it or it’s simply worth to be remembered without bloating it with an exhaustive blog entry.
Therefore, I want to give a more or less regular (let’s see how this works out) update on all these cool stuff one might find out there in the wilderness of the cyberspace.
Nowadays, a majority of modern life are numbers. Money you earn, money you spend, miles you drive, fly, run or ride by bike. There are many numbers you don’t make any use of. There are even more numbers you don’t think of. There are even numbers you don’t know of.
At the very end it is about what you make out of these numbers. Some time ago I started to run various kinds of data analysis.
For example, in 2012 I went 60 times to the gas station, spending 2774,77 € for gas. Never thought of it being that much. March was a crazy month, it seems I drove three to four times as much as in August where I used to be in vacation or October when I worked mainly from my home office. In November I started a new position, which might explain a new baseline around the 200 € mark – something I definitely should verify end of 2013.
I thought I try to pick the cheapest gas station around, however I just realized more than half of the time I went straight to Total, which is just around the corner. This is a clear indicator to compare prices in the future more in detail as there are better prices than Total offers most of the times.
It was not that hard to gather the data. Most effort went into how I should compare the data. Neither was the process of thinking about what the actual information might tell me that hard. However, it definitely shows you some ways of improvement for the future.
This is only a subset of data I am currently working on. If you are interested in more analysis, just stay tuned…
Currently I have started a new project and I am looking into some geo-related projects. NASA World Wind 1.4 is now available. World wind makes massive usage of .NET and DirectX and runs quite smooth under windows Vista. The data is also provided by Microsoft Research TerraServer-USA, hosting aerial photography and topographic maps.
Unfortunately, TerraServer provides only United States Geologically Survey (USGGS) data. Better images for local European location can be accessed using the Virtual Earth plug-in, available from here. A video of Virtual Earth in World wind can be found here. Unfortunately, the plug-in does not seem to work with the latest World Wind version.
With the updated plug-in for version 1.4 available also the Virtual Earth data can be displayed.
I found a quite useful overview of international system unit prefixes:
Factor Name Symbol Origin Derivation
2^10 kibi Ki kilobinary: (2^10)^1 kilo: (10^3)^1
2^20 mebi Mi megabinary: (2^10)^2 mega: (10^3)^2
2^30 gibi Gi gigabinary: (2^10)^3 giga: (10^3)^3
2^40 tebi Ti terabinary: (2^10)^4 tera: (10^3)^4
2^50 pebi Pi petabinary: (2^10)^5 peta: (10^3)^5
2^60 exbi Ei exabinary: (2^10)^6 exa: (10^3)^6
Examples and comparisons with system units prefixes
one kibibit 1 Kibit = 2^10 bit = 1024 bit
one kilobit 1 kbit = 10^3 bit = 1000 bit
one mebibyte 1 MiB = 2^20 B = 1 048 576 B
one megabyte 1 MB = 10^6 B = 1 000 000 B
one gibibyte 1 GiB = 2^30 B = 1 073 741 824 B
one gigabyte 1 GB = 10^9 B = 1 000 000 000 B