Table of Contents

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  1. Preface
  2. Components
  3. Business services
  4. File listeners
  5. Fixed-width file formats
  6. Hierarchical schemas
  7. Intelligent structure models
  8. Mapplets
  9. Saved queries
  10. Shared sequences
  11. User-defined functions

Components

Components

Troubleshooting intelligent structure models

Troubleshooting
intelligent structure model
s

Consider the following troubleshooting tips when you create
intelligent structure model
s.
Using differently structured files causes data loss.
If the
intelligent structure model
does not match the input file or only partially matches the input file, there might be data loss.
For example, you created a model for a sample file that contains rows with six fields of data,
computer ID
,
computer IP address
,
access URL
,
username
,
password
, and
access timestamp
. However, some of the input files contained rows with eight fields of data, that is a
computer ID
,
computer name
,
computer IP address
,
country of origin
,
access URL
,
username
,
password
,
access code
, and
access timestamp
. The data might be misidentified and some data might be designated as unidentified data.
If some input files contain more types of data than other input files, or different types of data, for best results create a sample file that contains all the different types of data.
Data from PDF forms was not modeled or parsed.
An
intelligent structure model
can model and parse the data within PDF form fields but not data outside the fields. A field title, or other data outside the field, will not be identified.
Data from Microsoft Word was not modeled or parsed.
An
intelligent structure model
can model and parse data within Microsoft Word tables. All other data is collected as unparsed data.
Error: Unsupported field names might cause data loss.
Do not use duplicate names for different elements.
If you use Big Data Management 10.2.1, ensure that the names of output groups follow Informatica Developer naming conventions. An element name must contain only English letters (A- Z, a-z), numerals (0-9), and underscores. Do not use reserved logical terms, and do not start element names with a number.
In later versions of Big Data Management or Data Engineering Integration,
Intelligent Structure Discovery
replaces special characters in element names with underscores and inserts underscores before element names that start with numerals and before element names that are reserved logical terms.


Updated August 03, 2020