How to Spot Common Salesforce Org Growing Pains

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I want to talk about what happens to a lot of orgs when they think about data

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management life

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cycles because we often start out with a strategy whether that's spoken or oft

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entimes unfortunately

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unspoken it's not really been consciously thought about when we start off with

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a new org and maybe

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small data sets and that kind of works for a while when the data is new or the

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data is still in

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development but over time orgs tend to balloon and volume and those strategies

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have to change or

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they at least have to be consciously set so I would love to talk about the

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challenges that you've

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encountered as your data storage grew. Lori can you tell us about your data

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storage growing over time

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and how that kind of created some hurdles for you? Sure and I think there we

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had we had two

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challenges specifically related to that we migrated away from a so we have a

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legacy sales force

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environment and as you can imagine there was data in there but we reduced the

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amount of user

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significantly and so the availability of data that we had in there kind of

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shrunk and so we had

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to figure out how we handled that data as we keep it around for historical

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purposes and how we get

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within our data consumption limits in that environment so we had that one and

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that was actually really

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high attachments and files were something we really had to be concerned about

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in that world so we had

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to deal with kind of that world just from a legacy perspective and then as we

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went into our new org

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you know as you mentioned over time things just started creeping up on the on

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the data side of the

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house and so we really started to outgrow our ability to do like the annual

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task of deleting

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data based on certain policies that we'd set right so we were out growing that

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you know pretty

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quickly over the last three years and we had to look at a different kind of

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continuous solution.

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Right so the manual deleting of data which you were doing to you know keep your

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storage down was

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becoming kind of untenable right yeah and tenable and frankly wasn't working

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because our data was

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out growing faster than we could you know delete some of the objects that we

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were okay with.