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You can read the PDF User Guide online and know in details how the app works
Data Extractor allows to extract data from files where is in raw sparse state and collect it inside a table ready to be exported for later use
Data is collected in records (rows) with custom specified fields (columns) inside a table. Data can be exported at any time.
It solves the problem that often advanced users have, the necessity to extract data available in text format on one or more files (often thousands and thousands of files) , and moving them inside a table or a database in an ordered and structured form with fields and records for archiving and successive processing.
Data extractor can parse thousands and thousands of file in few seconds and collect all the data inside these files using simple instructions on how to recognize data, how to extract them and where to put these data inside Data Extractor tables, ready to be exported.
When the data you want to extract are recognizable inside a text by a start label and the end of data by another label or a newline or return or a tab, Data Extractor can extract it and do in few seconds ,the job you would requires weeks or months to do.
Data Extractor provides all the tools to accomplish these specific tasks in a fast and smart way.
The app provides an internal database table where data can be collected.
Data are always available for export on disk in CVS (comma separated value) or TSV (tab separated value)
Name of custom fields can be used as first record during exportation.
The application is document based and any document can be customized for fast batch processing of large amount of data with specific sources, rules of extractions and custom destination fields.
The application includes a PDF user guide and an internal help with also 4 practical lessons on how to extract data from text files and put them inside a table the user can create and modify.
Due to the complexity of the operations we discovered that it is a lot easier to show to the user some examples of usage before explaining from a general point of view how the app works.
In this case learning by example works better
The user can download from our site the demo examples containing the documents and text files used for the 4 easy lessons
Data Extractor is useful in a large array of circumstances:
- Transform order or data in general you receive via email in a database records (Data Extractor can parse directly emails pointing at your mailbox on your Hard Disk)
- Collect order received as server output when not directly inserted inside a database
- Extract data from files one by one, also dragging them via Drag & Drop
- Convert data provided in one format to another when the first format uses a recognizable patter with labels to identify data fields
- Extract data from files where data are written all in one file with record separated just by a distinctive string
- Extract data from files where records are separated by newline with fields all in one line identified just by labels
- Extract data from text document where misleading labels can result in extracting the wrong data, thanks to the use of special tag usable to instruct Data Extractor where to really start collect data
- Parse files only if they respond to certain characteristic
- Extract data only if they respond to certain characteristic
- Extract data also when it is specified by more then one label (it can put different extraction in the same destination field)
Data Extractor can works entirely in background
- Is always responsive also during extraction from folder with nested thousands of files at any nested level and at any moment the user can stop the process
- Optimized for Lion and Mountain Lion, is able to use the latest technologies available: Resume, Auto Save, Versions and Full screen
- Sandbox enabled using the latest technology to manage external files in a sandbox environment