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If you are in a position to design the data life cycle (perhaps as part of a migration to a new technology, or a brand new data collection initiative) you have an opportunity to design for greater impact and better quality.
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In the first column, focus on value without worrying about resources. In the second column, consider the resources that would be needed.
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PlanValueResources
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What are the objectives for data collection?
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What business rules apply?
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What standards are used with related datasets, both internal and external to your agency or government?
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What high-level technology systems and programs are available (or could be procured) for the planned database?
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Obtain
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What data can be collected? How might additional data be valuable?
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How might more accurate or more precise data collection be valuable?
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Store and Share
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How might archives or historical snapshots be valuable?
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With what systems should the new system be compatible?
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What liabilities might storing the data create?
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Maintain
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How important is it to keep the data up-to-date? On what schedule?
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How might ongoing quality monitoring be valuable?
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What are the timeframes for recovery of data in case of problems?
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Apply
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Who are all the stakeholders? What do they want from the data?
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Who are all the users of the data? What have they complained about, or complimented, in existing systems?
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What kind of analyses of the data might be valuable? What criteria for data are required or desired by people who perform such analysis?
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Destroy
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When (if ever) is it necessary or desirable to destroy the data?
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What (if any) retention requirements apply?
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Contact the author at sfsinger@campaignscientific.com, @sfsinger, 267-414-3119. Guide available for download at bit.ly/DQGuide. Submit feedback at bit.ly/SingleStepsFeedback
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