From the course: Data Quality: Core Concepts
Data quality introduction
From the course: Data Quality: Core Concepts
Data quality introduction
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- In this chapter, we'll define data quality, go over the nine dimensions of data quality, and finally, go through a thought exercise, where we take a business strategy objective and tie it to a data quality initiative.
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Contents
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Data quality introduction13s
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Impact of poor data quality3m 40s
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(Locked)
Defining data quality4m 48s
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(Locked)
Data quality dimensions: Intro1m 1s
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(Locked)
DQ dimensions: Validity, completeness, consistency2m 36s
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(Locked)
DQ dimensions: Integrity, timeliness, currency2m 41s
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(Locked)
DQ dimensions: Reasonableness, uniqueness, accuracy3m
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(Locked)
Common data quality assessment frameworks2m 26s
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(Locked)
Connecting data quality to business outcomes: Intro1m 22s
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(Locked)
Thought exercise: Ecommerce41s
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(Locked)
Thought exercise: Understand the business model44s
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(Locked)
Thought exercise: Map your data lifecycle1m 32s
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(Locked)
Thought exercise: Identify your stakeholders1m 12s
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Thought exercise: Evaluate how stakeholders drive revenue41s
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(Locked)
Thought exercise: Assess how DQ impacts revenue and risk48s
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(Locked)
Thought exercise: Synthesize research and communicate ROI3m 15s
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