From the course: Data Quality: Core Concepts
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Thought exercise: Assess how DQ impacts revenue and risk
From the course: Data Quality: Core Concepts
Thought exercise: Assess how DQ impacts revenue and risk
- [Instructor] In the fifth step, we assess how data quality impacts revenue and risk for these teams. So for the carts team, they focus on logging within the carts and it's essential for machine learning and product analytics. The recommendations team takes this data where increase ML accuracy increases sales 'cause they're recommending better products For the shopping workflows team, reduce UX friction also increases sales, and they depend heavily on the logging from the carts team. And then finally, for the vendor relations team, increase sales results, increase vendor use. If vendors are selling more products to customers, they're going to be happy and stay on the platform. Finally, we're going to tie this all together in the next video to synthesize that as a proposal for leadership to invest into the 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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(Locked)
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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