Troubleshooting Date and Time Conversion Issues in FME

Working with date and time data can be tricky, especially when dealing with different formats. This article addresses a common challenge faced by FME (Feature Manipulation Engine) users: converting dates from various Excel formats into a consistent format for further processing.

The Problem: Inconsistent Date Formats in Excel

Many FME users encounter situations where date attributes in Excel files have varying formats. One file might have dates in the dd.mm.yyyy format (e.g., 01.02.2010), while another uses yyyymmdd (e.g., 20100304). This inconsistency can cause problems when you need to perform operations based on a specific date format.

The Goal: Standardizing to yyyymmdd Format

The primary objective is to convert all incoming date attributes, regardless of their original format, into the yyyymmdd format within FME. This standardization ensures that subsequent transformer conditions and processes work correctly.

Initial Attempts and Challenges

Using the DateTimeConverter transformer with a specified input format (e.g., %d.%m.%Y$) and an output format (%Y%m%d) might seem like a direct solution. However, when FME encounters dates in a different format, the conversion fails, resulting in null values in the rejected output.

Solutions and Strategies

Here's a breakdown of effective strategies to handle diverse date formats in FME:

1. Data Inspection is Key

• Always Verify: Never rely solely on how Excel displays dates. The underlying data might be different.
• FME Data Inspector: Use the FME Data Inspector to examine the actual values of the date attributes. This will reveal the true format and help you understand the variations you need to handle.

2. Conditional Conversion with the Tester Transformer

• Identify Patterns: Use the Tester transformer to identify date formats based on specific patterns. For example, check if the attribute contains a "." (period). If it does, it likely follows the dd.mm.yyyy format.
• Route to Converters: Based on the test results, route the data to different DateTimeConverter transformers, each configured with the appropriate input format.
• Combine Results: After conversion, use a FeatureMerger or similar transformer to bring the data back together.

3. Dynamic Date Parsing with AttributeCreator

• @DateTimeParse() Function: Utilize the @DateTimeParse() function within an AttributeCreator transformer to dynamically parse dates.
• FME|ISO Format: Start by attempting to parse the date using the FME|ISO option, which tries to automatically detect common FME and ISO date formats.
• Conditional Values: Check for NULL values after the initial parse. If a date couldn't be parsed, it indicates that it's in a different format.
• Iterative Parsing: Add more lines in the AttributeCreator with different variations of year, month, and day arrangements in the @DateTimeParse() function to handle other potential formats.

4. Utilizing FME and ISO Date/Time Formats

• Supported Formats: FME can automatically detect certain date/time formats based on FME and ISO standards.
• Documentation: Refer to the official FME documentation for a comprehensive list of supported formats.

5. Addressing Ambiguity

• Month-First vs. Day-First: Be aware of ambiguity issues, especially when dealing with formats where the day and month positions are not clear (e.g., 01/02/2023 could be January 2nd or February 1st).
• Avoid Auto-Detection: Auto-detecting the format can lead to incorrect conversions. Be explicit with your date format definitions whenever possible.

6. Data Governance and Standardization

• Enforce Standards: Implement data governance practices to ensure that incoming data adheres to recognized data standards, preferably ISO formats.
• Source System Control: If possible, work with the source systems (e.g., the creators of the Excel files) to enforce a consistent date format.

Example FME Workflow Snippet

# Example using Tester and DateTimeConverter

Tester:
  - Condition: Attribute contains "." (period)
    - True: DateTimeConverter_DMY
    - False: DateTimeConverter_YMD

DateTimeConverter_DMY:
  - Input Format: %d.%m.%Y$
  - Output Format: %Y%m%d

DateTimeConverter_YMD:
  - Input Format: %Y%m%d
  - Output Format: %Y%m%d

Key Considerations:

• Error Handling: Implement robust error handling to catch any dates that cannot be converted.
• Logging: Log the original and converted dates for auditing and debugging.
• Documentation: Document all assumptions about the format and how you handle different formats.

By combining these strategies, you can create a robust FME workflow that effectively handles various date formats and converts them into a consistent yyyymmdd format, ensuring the reliability of your data processing pipelines. Remember to prioritize data inspection, use conditional logic, and consider implementing data governance practices to prevent future inconsistencies.