Rons Data Stream - Feature List

General Features

		Jobs: set up of data sources, formats and destinations
		Jobs files can be stored with the data (if the data is in a directory), or separately if needed, and run at the click of a button or from the command line.
		Cleaners: set up of cleaning rules to process data
		One or more Cleaners can be created, named, saved and re-used with multiple Jobs as often as needed.
		Rules: the list of operations to perform on the data
		Numerous column, row and cell operations are combined easily within the cleaner. See List of Rules below.
		Loads data from multiple available sources
		See Source and Destination Information below.
		Outputs to multiple formats
		Source and destination formats can be configured for simple file conversion. See Source and Destination Information below.
		Quick Job
		An alternative window for quickly setting up a cleaning Job. The Quick Job can even be saved as a full Job.
		Preview Screen
		Essential for building cleaning tasks. Clear comparison of the original data with the processed one.
		Log files Output
		Essential for finding errors on large files.
		Full control over text format
		Full text encoding supported: Utf-7, Utf-8, Utf-16 and Utf-32 (both big endian and little endian), with automatic detection.

List of Cleaning rules

The (growing) list of available data operations in Rons Data Stream are shown in the table below.

• Column Processors
  • Add Column(s)
  • Update Column
  • Copy Columns
  • Move Columns
  • Delete Columns
  • Merge Columns
  • Split Columns
• Row Processor
  • Add Row
  • Delete Row
  • Split Row
• Cell Processors
  • Add Text
  • Add Random Text
  • Pad Text
  • Remove Text
  • Replace Text
  • Reverse Text
  • Add Space
  • Remove Space
  • Add Numbers
  • Remove Numbers
  • Replace Numbers
  • Add Date Time
  • Replace Date Time
  • Change Case
  • Split Name
  • HTML Encode
  • HTML Extract
  • Fill Lookup
  • Lookup Replace

Sources and Destinations

Rons Data Stream started life as the automation arm of Rons CSV Editor, and as such currently supports text based data formats. It soon became clear that our customers needed support for more data formats, the status of which is indicated in the table below.