# How to analyze Fibery DBs to discover correlations in data?

**URL:** <https://community.fibery.io/t/how-to-analyze-fibery-dbs-to-discover-correlations-in-data/4365>\
**Category:** Get Help\
**Created:** [April 24, 2023, 2:45am UTC](https://community.fibery.io/t/how-to-analyze-fibery-dbs-to-discover-correlations-in-data/4365 "2023-04-24T02:45:10Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![Matt\_Blais](https://sea2.discourse-cdn.com/flex020/user_avatar/community.fibery.io/matt_blais/32/1464_2.png) [@Matt\_Blais](https://community.fibery.io/u/Matt_Blais)\
**Post date:** [April 24, 2023, 2:45am UTC](https://community.fibery.io/t/how-to-analyze-fibery-dbs-to-discover-correlations-in-data/4365/1 "2023-04-24T02:45:10Z")

</div>

I have a Fibery workspace with data imported from many individual Zoho CRM accounts - with DBs like Users, Leads, Tasks, Accounts, Contacts, Campaigns, Deals, Calls.

Additionally, each account may be marked as “Failed” (meaning the account’s client was ultimately not satisfied with the results).

My goal is to create a metric to measure the likelihood that an account will become Failed in the near future.

Is it possible to direct Fibery’s AI to analyze all the data for the best correlations for predicting whether an account will become Failed?

And if not, can anyone suggest a tool that is well-suited to this task?