Forum Discussion
Increased data size after new date column
- 1 year ago
Hi HR3038511
The increase in your model size is likely due to the way VertiPaq handles date columns, especially when they include both date and time components. Here are a few best practices to help reduce the size:
Disable Auto Date/Time:
Go to File > Options > Data Load and uncheck the Auto Date/Time option. This feature automatically generates hidden date tables for each date column, which can significantly inflate your model size if not required.
Split Date and Time:If your changeddate column includes both date and time components, consider splitting it into two separate columns:
One column for the date only.
Another column for the time only.
This reduces cardinality (the number of unique values) in each column, which is a key factor in model size.
Optimize Storage Format:For the date-only column, ensure the column is formatted as a Date data type, not DateTime.
If time is stored in the second column, format it as Time.
Remove Unnecessary Precision:If the time component has a precision that isn't necessary (e.g., milliseconds), round it or remove it entirely to further reduce cardinality.
Consider Aggregations:If granular date-time values aren't necessary for analysis, you could aggregate the data (e.g., by day or hour) and store only the aggregated date values.
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Hey ,
Please Look for following points
- Remove the time portion from the column if not needed, keeping only the date.
- Convert the column to an integer format, such as YYYYMMDD, to save space.
- Change the data type to Date instead of DateTime if time values are unnecessary.
- Aggregate or summarize the data to a higher level, such as monthly or yearly, if detailed dates are not required.
- Archive older data into a separate dataset if it is less frequently accessed.
- Sort the column to improve VertiPaq compression efficiency.
Best Regards,
Govind Sapkade
Data Analyst | Power BI Enthusiast | Microsoft PL 300 Certified Power BI Data Analyst | MS Fabric Enthusiast
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