How do unnecessary columns affect performance?

< 1 min read

Unnecessary columns negatively impact performance by increasing data volume.
In one project, a fact table included 25 columns, but only 10 were used in reporting.
The extra columns increased dataset size and slowed down refresh time.
It consumed more memory in the BI tool and affected load performance.
Network transfer time also increased when pulling data from the database.
Wide tables make query processing heavier, especially during joins.
After removing unused columns, report performance improved noticeably.
So selecting only required columns keeps the model efficient and scalable.

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