title: Numeric value 'abc_0011O00001y31VpQAI' is not recognized in Snowflake
body: <p>(Opening the following on behalf of a Snowflake client...)</p>
  
  <hr>
  
  <p>When I try to insert into the table it threw below error:</p>
  
  <blockquote>
    <p>Numeric value 'abc_0011O00001y31VpQAI' is not recognized</p>
  </blockquote>
  
  <p>Have check the table DDL and found only 3 columns defined as NUMBER and rest as VARCHAR.</p>
  
  <p>I checked the SELECT query and didnot find any string value in those NUMBER Datatype columns. Also tried searching in all the Varchar columns for the value 'abc_0011O00001y31VpQAI' , I didn't find any</p>
  
  <p>I know one thing Snowflake doesn't always shows correct error. Am I missing anything here? Is there any way to fix it?</p>
  
  <p>Both <code>COL4_MRR</code> and <code>COL5_QUANTITY</code> are <code>NUMBER</code></p>
  
  <pre class="lang-sql prettyprint-override"><code>    INSERT INTO TABLE
      (COL1_DATE, COL2_CD, COL3_CUST_NAME, COL3_LOC_NAME,COL4_MRR,COL5_QUANTITY)
  
      SELECT 
       '2019-10-03' AS COL1_DATE ,
         'AE' AS COL2_CD
         ,CUSTOMER_NAME AS COL3_CUST_NAME
         ,LOCATION_NAME AS COL3_LOC_NAME
         ,MRR_BILLED as COL4_MRR
         ,QTY_BILLED as COL5_QUANTITY
      FROM SCHEMA.V_TABLEA
      union all 
              SELECT 
       '2019-10-03' AS COL1_DATE ,
         'BE' AS COL2_CD
         ,CUSTOMER_NAME AS COL3_CUST_NAME
         ,LOCATION_NAME AS COL3_LOC_NAME
         ,NULL as COL4_MRR
         ,QTY_BILLED as COL5_QUANTITY
      FROM SCHEMA.V_TABLEB
  </code></pre>
  
  <p>I created a table_D same as original TABLE and tried inserting into it , it worked fine . Then Inserted into Original TABLE from table_D , it worked again .</p>
  
  <p>Deleted those rows from original TABLE and reran the job , it worked fine.</p>
  
  <p>There was no issue with data as all was Number only, I even tried with <code>TRY_TO_NUMBER</code> too.  It inserted the data without any changes to the code.</p>
  
  <p>...............</p>
  
  <p>Client is currently waiting on a next day run to re-test to determine if this is either a bug or an issue with their data.  In the meantime, we are interested to see if anyone else has run into similar challenges and have a viable recommendation.  THANK YOU.</p>