Troubleshooting Guide

the following guide can be used to troubleshoot your mapping and dataset conversion configuration if you come across any errors or failures, you can follow this guide in a top down approach to try and identify the issue general troubleshooting duplicate assets duplicate assets can cause issues in conversions the validator function can be used to check for duplicates to run the validator, select an asset group and click validate from the toolbar duplicate assets are indicated by a critical severity flag and must be fixed before running the conversion check the source data as the output data is dependent on the source data, users should always check that the source data is as expected in the source application for example, check the following is correct in the source data the name the number of records the data in the columns with larger datasets, it is good practice to download the csv and check it in excel filter columns and values to ensure you have full visibility of the data manage complexity inserting multiple complex source dataset mappings often leads to problems that are hard to troubleshoot it is not advisable to mix two types of source dataset mappings for example, one horizontal mapping and one horizontal to vertical mapping in one dataset results in a very complex variable/valuelist level mapping it is better to split these mappings into parallel datasets then combine the outputs failed conversions check the status of the conversion from the toolbar, data > view conversions can be used to view details of previous and current conversion tasks generally, the following can cause a conversion task to fail empty datasets (i e no data) datasets with no variables (no variables are referenced by the dataset) duplicate column names within a csv when viewing the conversion tasks logs, the following errors may cause the conversion to fail asg001 asset group is missing the standard name asg002 asset group is missing the standard version dom0013 sort output rows is missing variables or has incorrect variables dom0014 deduplicate/sort output rows is missing variables or has incorrect variables dom0015 incorrect pivot variable var0027 copy mapping has invalid variable references uploading data the following must be considered when uploading data do not use create asset group function, go to an existing asset group and select data > upload >select file uploads can take a while, especially if they are large or if you’re overwriting existing data csv files must use utf 8 encoding non utf 8 characters within a csv file may cause the upload to stop at that row ( tip use an utf 8 editor like notepad++ or a conversion tool like stattransfer to force utf 8 character encoding) dataset troubleshooting scenario the dataset outputs no rows or an incorrect number of rows check the following dataset mapper properties source dataset identifier ensure that you have populated the source dataset identifier property with the correct reference to a source dataset source dataset include row mappings if you are using the include rows mapping at the source dataset level then you can check if the condition here is correct for example, you may want to include rows where a source variable is not equal to blank if this column in the source dataset is blank, then this will cause the whole dataset to have no rows source dataset pivot variable if you are using the pivot functionality by specifying the pivot variable at the source dataset level, ensure that you have selected the correct variable it must be in the same dataset as the source dataset and there should be values on that variable to facilitate the pivot process double check the mappings on the values as blank pivot values will not create a row on output so if some or all of the value mappings are correct, the dataset will have fewer or no rows on output variable troubleshooting scenario columns in your target dataset are not correct or are blank check the following dataset mapper properties source type source variable source columns are mapped from variable properties using source type > source variable if the output column is blank, check that the value entered as the source variable matches a column in the source dataset source type source variable (multi stage mappings) for sdtm mappings, there can be multiple stages to convert raw data to sdtm ( for example, source data > vedc vedc > sdtm+ sdtm+ > sdtm if an output column is blank, check the direct source mapping continue working backwards in the chain until you find where the issue is source type function when using a function mapping, ensure that you are using the correct parameters for that function when working with functions, please refer to docid\ f29bxyuary2sq59lz9uis you can also see examples of some common functions in the docid\ dkmua9njlzyseskhiiz0d dataset lookup source when using the dataset lookup mapping, if you get unexpected or blank outputs, check that the when conditions are correct check the data in your source and the lookup data to make sure that source and lookup variables are in the same format