Free data quality data profiling software for windows

We all know that JPG use lose compression, so anything you save is always in exact terms worse than original. It may not look like because of the way it is compressed but it is. And it is logical that if we later load JPG and then save again the degradation goes of course further.
Right now I can tell you the most degradation will be probably in the first round - from the original to the first JPG. If we load the JPG and save again this time the data are already somehow processed by first round so the degradation wont be as strong as first time. Of course there is quality loss on the second time and if we load and save it again and again we will soon realize the quality loss is adding up.
Loss is adding up but not as many people think - if we use twice 75% first time then 75% second time it doesnt mean that the second round is equal to 55% of original quality (75% of first 75%). There is some loss but far less. So it doesnt work like your taxes.
If we consider all this then it start to be obvious that if we ever need re-save a JPG we should use the same quality settings as a first time. Why not bigger? Because by bigger Q second time we wont gain anything at all! The file is already degraded by first round and these data will not be returned by simply setting higher quality next round. Setting the Q second time higher than first time will just make the JPG bigger, but still worse than the first.
The simple answer is: If you need to load and save a JPEG you should use the same Quality settings as was used on the JPG when it was first created.
We of course assume that we work on the same pixels. If you for example load an image of dog completely repaint it into image of sunflower then of course you can also choose any quality setting you like (and also a doctor). But this isnt the case in 99.9%
Talking now about digital cameras - our main topic: After we make a change on the image from digital camera we should save it with the same Quality settings as it was produced from the raw data inside the camera.

Apatar is the open source leader in data mashup integration. It is the first company to bring open source data mashups solutions. Apatar performs a wide range of ETL (Extract, Transform, and Load) functions and allows easily join your desktop data with the web.
Connectors include: MySQL, PostreSQL, Apatar is the open source leader in data mashup integration, MS SQL, Amazon, Compiere, SugarCRM, Oracle, PostgreSQL, XML, CSV and even Flickr.
No coding is required to accomplish even a complex integration. Benefits: Reduce integration cost, Improve data quality, Shorten implementation time, Reduce maintenance costs, Eliminate custom coding.
Apatar brings a low-cost, on-demand, open source data integration to the masses where users can publish, share and re-use integration mappings over the web.
100% Java, Apatar is multi-platform application with scalable architecture for large deployments. Ideal for integrating on-premise data with the web.