Recommendations overlap each other, so the final “potential savings” is not accurate because it is not achievable.
for example, On our demo project, we are showing savings of 88%! ( 3170 / 3643)
is it possible that current logic will show customers more than 100% of savings?
I suggest:
1. separating the recommendations into those categories
Schema design - implementing this change won’t change your business logic but might save you money.
Change the logic - change the way you are using big query. If it fits your business, you might be able to reduce costs (limit query job, enforce partitioning, delete old data)
Use superquery - it will cache data so that you will scan less in bigquery.
2. Present the impact by order of priority or order of magnitude of savings. This will have a similar impact and avoid presenting inaccurate savings.
Potential cost savings exist, depending on the nature of your business (limit query job, enforce partitioning, delete old data) Use superquery to reduce the amount of data scanned in 2048 bigquery by caching it. Show the effects in descending order of importance or cost reduction. Savings projections won't be skewed in any way, and the effect will be the same .
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