Data Extractor allows to extract data in a sparse format contained inside files and collect them in an internal structured table
Collected data can be exported at any time in various format (CSV, TSV, HTML, Custom).
Data Extractor is perfect also to collect data from emails, it works with Mail.app emails.
Data extractor can parse thousands and thousands of file in few seconds and collect all the raw data inside.
It uses simple instructions about how to recognize data, how to extract them and where to put these data inside a structured table, 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 or even years to do by hand.
Data Extractor provides all the knowledge to accomplish these specific tasks in a fast and smart way inside a beautiful and elegant, Mac only, native application.
The application provides an internal database table, where the user can create how many columns she/he likes, where data can be collected.
Data are always available for export on disk in CVS (comma separated value), TSV (tab separated value) or html table format.
Name of custom fields can be used as first record during exportation (for successive smart importing).
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.
Creating many documents the user can create as many custom 'extraction set' he needs to extract from different files and with different extraction rules.
The application includes a PDF user guide with also 4 practical lessons with demo documents (on our site) on how to extract data from text files and put them inside a custom, user created table.
Due to the complexity of the operations we know 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.
• 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
• Perfect to extract data from emails. Works perfectly with emails by Mail.app
• Can process folders extracting from all the files inside nested to any level
• Convert data provided in one format to another when the first format uses a recognizable patter with labels to identify data fields
• Adjustable data columns positions
• 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 with non unique, ambiguous tags , using special tags usable to instruct Data Extractor where to really start collect data
• Parse files only if they respond to certain characteristics
• Extract data only if they respond to certain characteristics
• Extract data also when it is specified by more then one label (it can put different extraction in the same destination field)
• Can use 'Case Sensitive' option for data tags
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 macOS 10.10, macOS 10.11, macOS 10.12 (Sierra) and macOS 10.13 (High Sierra)
Uses all the latest technologies available: Resume, Auto Save, Versions and Full screen
You can test an unlicensed version from our site before buying! Visit us at TensionSoftware.com
• New improved layout of the 'Run' zone offering a better view of the elaboration flow
• More data offered inside the 'Run' zone about file processed, skipped then accepted and rejected and record and fields inserted in the internal database
• Various bug fixes
• Code optimizations