Hi, I'm Ask INFA!
What would you like to know?
ASK INFAPreview
Please to access Ask INFA.

Table of Contents

Search

  1. Preface
  2. Working with Transformations
  3. Address Validator Transformation
  4. Aggregator Transformation
  5. Association Transformation
  6. Bad Record Exception Transformation
  7. Case Converter Transformation
  8. Classifier Transformation
  9. Cleanse transformation
  10. Comparison Transformation
  11. Custom Transformation
  12. Custom Transformation Functions
  13. Consolidation Transformation
  14. Data Masking Transformation
  15. Data Masking Examples
  16. Decision Transformation
  17. Duplicate Record Exception Transformation
  18. Dynamic Lookup Cache
  19. Expression Transformation
  20. External Procedure Transformation
  21. Filter Transformation
  22. HTTP Transformation
  23. Identity Resolution Transformation
  24. Java Transformation
  25. Java Transformation API Reference
  26. Java Expressions
  27. Java Transformation Example
  28. Joiner Transformation
  29. Key Generator Transformation
  30. Labeler Transformation
  31. Lookup Transformation
  32. Lookup Caches
  33. Match Transformation
  34. Match Transformations in Field Analysis
  35. Match Transformations in Identity Analysis
  36. Merge Transformation
  37. Normalizer Transformation
  38. Parser Transformation
  39. Rank Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. Source Qualifier Transformation
  44. SQL Transformation
  45. Using the SQL Transformation in a Mapping
  46. Stored Procedure Transformation
  47. Standardizer Transformation
  48. Transaction Control Transformation
  49. Union Transformation
  50. Unstructured Data Transformation
  51. Update Strategy Transformation
  52. Weighted Average Transformation
  53. XML Transformations

Transformation Guide

Transformation Guide

Parsing Word Documents for Relational Tables

Parsing Word Documents for Relational Tables

You can extract order information from a Microsoft Word document and write the order information to an order header table and an order detail table. Configure an Unstructured Data transformation to call a Data Transformation parser service and pass the name of each Word document to parse.
Data Transformation
Engine opens the Word document, parses it, and returns the rows to the Unstructured Data transformation. The Unstructured Data transformation passes the order header and order details to the relational targets.
The mapping has the following objects:
  • Source Qualifier transformation. Passes each Microsoft Word file name to the Unstructured Data transformation. The source file name contains the complete path to the file that contains order information.
  • Unstructured Data transformation. The input type is file. The output type is buffer. The transformation contains an order header output group and an order detail output group. The groups have a primary key-foreign key relationship.
    The Unstructured Data transformation receives the source file name in the InputBuffer port. It passes the name to
    Data Transformation
    Engine.
    Data Transformation
    Engine runs a parser service to extract the order header and order detail rows from the Word document.
    Data Transformation
    Engine returns the data to the Unstructured Data transformation. The Unstructured Data transformation passes data from the order header group and order detail group to the relational targets.
  • Relational targets. Receive the rows from the Unstructured Data transformation.

0 COMMENTS

We’d like to hear from you!