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Hey all,
I'm working with huge data sets.I have a challenge with the age dataset, as the data is a mix of age in hours, months, and years, which causes an error when importing it to Power BI Desktop. I need help on how to categorize /format this data so that I'm able to import the entire data without an error.
Thanks for all your help.
Hi Peris,
Thank you for being a part of the Microsoft Fabric Community.
The user is working with a dataset where "age" values are recorded inconsistently in hours, months, and years. This inconsistency leads to errors when importing the data into Power BI Desktop. The user seeks guidance on standardizing or categorizing this mixed-format age data for error-free import and usage in Power BI.
We need to convert all age values into a single, consistent unit (such as years, months, or hours) before importing into Power BI. This will help avoid data type errors and ensure accurate analysis and visualization.
If standardization before import is not feasible, the user may need to create a new column in Power Query or Power BI to identify the unit for each age value or transform all values to a common unit using conditional logic.
The goal is to ensure the dataset can be imported into Power BI Desktop without errors due to mixed data types or formats.
I hope my suggestions provided valuable insights. If you have any further questions, don’t hesitate to ask in a follow-up message.
If this post helped, please mark it as "Accept as Solution" so others can benefit as well.Best regards,
Sahasra.
4 Replies
Hi Peris,
Thank you for being a part of the Microsoft Fabric Community.
The user is working with a dataset where "age" values are recorded inconsistently in hours, months, and years. This inconsistency leads to errors when importing the data into Power BI Desktop. The user seeks guidance on standardizing or categorizing this mixed-format age data for error-free import and usage in Power BI.
We need to convert all age values into a single, consistent unit (such as years, months, or hours) before importing into Power BI. This will help avoid data type errors and ensure accurate analysis and visualization.
If standardization before import is not feasible, the user may need to create a new column in Power Query or Power BI to identify the unit for each age value or transform all values to a common unit using conditional logic.
The goal is to ensure the dataset can be imported into Power BI Desktop without errors due to mixed data types or formats.
I hope my suggestions provided valuable insights. If you have any further questions, don’t hesitate to ask in a follow-up message.
If this post helped, please mark it as "Accept as Solution" so others can benefit as well.Best regards,
Sahasra.Hi Peris,
we haven't heard back from you regarding our last response and wanted to check if your issue has been resolved.If our response addressed by the community member for your query, please mark it as Accept Answer and give us Kudos. Should you have any further questions, feel free to reach out.
Thank you for being a part of the Microsoft Fabric Community Forum!Hi Peris,
We wanted to follow up since we haven't heard back from you regarding our last response. We hope your issue has been resolved.
If my answer resolved your query, please mark it as "Accept Answer" and give Kudos if it was helpful.
If you need any further assistance, feel free to reach out.
Thank you for being a valued member of the Microsoft Fabric Community Forum!