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Lachu1935's avatar
Lachu1935
Regular Visitor
7 months ago
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One Lake

Hi Team,   While uploading the data file to One Lake, I noticed that the data types for some columns were automatically recognized incorrectly. For example, my date column was mistakenly iden...
one lake
  • v-achippa's avatar
    v-achippa
    7 months ago

    Hi Lachu1935,

     

    Thank you for reaching out to Microsoft Fabric Community.

     

    Thank you Cookistador, chris_andrews and deborshi_nag for the prompt response. 

     

    As we haven’t heard back from you, we wanted to kindly follow up to check if the solution provided by the user's for the issue worked? or let us know if you need any further assistance.

     

    Thanks and regards,

    Anjan Kumar Chippa

chris_andrews's avatar
chris_andrews
Icon for Advocate I rankAdvocate I
7 months ago

Hi Lachu1935 ,

 

The issue here is that Fabric will not reliably auto-detect ambiguous date types (non ISO dates). As you are importing as a csv it will struggle to identify your dates as dates, read them as a string and format as text.

 

The solution here is to do one of the following:

  1. Structure your dates in your source data to a common ISO format like 2026-01-30 (yyyy‑mm‑dd)
  2. Change the column format using a notebook as Cookistador suggests (but this seems to be not working)
  3. Bring your data in using Dataflow Gen2 and using the Power Query editor to change the column format

I would personally get into the habit of using ISO date formats in data reporting if possible. You will have far less trouble when ingesting and transforming data. 

 

EDIT:

Have you tried Data Wrangler in notebooks? This assists you in transforming data within notebooks.

 

df = spark.read.option("header", "true").csv("Files/myfolder/myfile.csv")

display(df)

Accelerate Data Prep with Data Wrangler - Microsoft Fabric | Microsoft Learn