Text Mapping

Powerful Any-to-Any Conversion Tool

Drag-and-drop mapping between components
Text to XML, databases, JSON, EDI, XBRL, and more
PDF Data Extractor
Support for CSV, FLF, and flat files
Data processing functions & visual function builder

FlexText for defining text parsing rules
Map flat files to or from complex data structures
Combine multiple sources
Instant data transformation
Automate conversion with MapForce Server

Creating a Text Mapping

Altova MapForce includes flexible support for integrating flat files with XML, databases, EDI, Excel, PDF, XBRL, and other data.

Flat files such as CSV and text documents are used by many different applications and are often employed as an exchange format between dissimilar programs. Many organizations continue to utilize legacy software that produces output in the form of text files. Integrating these flat files and text documents with other data formats in a modern computing environment is increasingly difficult.

MapForce supports flat files as both a source and target of any mapping. MapForce does not limit you to one-to-one mappings: you can mix multiple sources and multiple targets to map any combination of data formats.

When you load a CSV or FLF text file into a MapForce data mapping design, you can append, insert, and remove fields as well as change field header names and values as required before importing the file.

You can also choose to handle empty text file fields as empty elements in the data target, or you can treat empty fields as absent so they are not rendered in the target data structure.

Once you have loaded all of the content models required for your mapping, simply drag connecting lines between the source and target structures to connect matching elements.

MapForce includes a comprehensive library of data processing functions for filtering data based on Boolean conditions or manipulating numeric or string data in flat files as they are converted.

Parse Text Files with FlexText

MapForce includes the unique FlexText utility for parsing and converting data from non-standard or highly-complex, legacy text files such as mainframe text reports, text-based log files, and so on, in mapping designs. With its visual interface, FlexText lets you insert an existing text file and extract the portions you want to convert in the MapForce mapping interface.

FlexText produces a template that is then loaded into the mapping design, where individual text nodes can be converted to any combination of XML, database, PDF, EDI, XBRL, flat file, Excel, JSON, and/or Web service data. By saving the configuration you create in FlexText, you can reuse the same template to convert multiple text files in multiple mappings.

The data mapping tool includes FlexText for text file parsing

FlexText allows you to create rules for text file conversion templates. When you open a text file in the FlexText interface, the file is displayed in two blocks. The root block represents the original file, while the operation block (to its right) displays the data of the file in real-time as you extract the data you need.

The result of every operation you make is visible in real-time, so you can immediately see if you’ve achieved the desired result.

Legacy text files may contain useful data in CSV or FLF formats inside a more complex flat file. FlexText allows you to directly extract such data using the CSV and FLF operations. After applying Split and other operations, you can store remaining CSV- or FLF-formatted fields by configuring the field names, lengths, etc.

How to Parse Legacy Text Files with FlexText

Extract Relevant Data

FlexText allows you to isolate the data you need to access by removing non-relevant text, characters, and whitespace using split commands. Each split presents your data in two new blocks: one that contains the data you have split out, and another displays the modified view of your converted file. You can immediately see the result of each operation you perform.

Node, Ignore, Switch, and Regular Expressions

FlexText supports Node and Ignore operations for further flexibility in constructing the information tree. An Ignore operation marks a block of text as irrelevant for conversion purposes and instructs MapForce to ignore it. The Node operation creates a new node in the information tree in MapForce so that you can properly represent the hierarchical nature of your text data when needed.

The Switch operation allows you to define multiple conditions for a single block of text. Data in the text file is passed to the associated container for use in your MapForce conversion only if it meets a defined condition.

FlexText also supports for regular expressions. For instance, an input file could be a system-generated report with numbers and letter codes in the left margin that indicate record types where a sequence of any five digits followed “O” indicates the beginning of a new section for one office location.

Automate Text Conversion

Once your data mapping project is complete, MapForce will convert the data so you can view and save results instantly. You can also automate text conversion and transformation processes via MapForce Server.

“Altova MapForce provides excellent mapping capabilities that we can seamlessly embed within our core products. The extensible nature of the product means it covers all of our solution requirements.”

Scott Redford Visionware

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