From the course: Data Quality: Core Concepts
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Common data quality assessment frameworks
From the course: Data Quality: Core Concepts
Common data quality assessment frameworks
- [Instructor] In this video, we're going to be going over the common data quality assessment frameworks that you can choose from to implement within your organization. And forewarned, there are a lot. This is only a fraction of them available. And this table comes from a really great article, which I'll pull up right now, called "An Overview of Data Quality Frameworks" by Corinna Cichy and Stefan Rass. And this is probably one of the best articles that I came across because it gives an industry overview of the various frameworks that there are when they came out and how various companies are using them. I've included a link to this article that you can read yourself that I highly recommend you checking out. If you find this a little overwhelming looking at them, I agree with you. There's a whole bunch of different directions. And again, it's really tied to what the business needs. In future slides, I will go over how to best choose an assessment for you. One thing I do want to call…
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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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Data quality dimensions: Intro1m 1s
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DQ dimensions: Validity, completeness, consistency2m 36s
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DQ dimensions: Integrity, timeliness, currency2m 41s
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DQ dimensions: Reasonableness, uniqueness, accuracy3m
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Common data quality assessment frameworks2m 26s
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Connecting data quality to business outcomes: Intro1m 22s
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Thought exercise: Ecommerce41s
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Thought exercise: Understand the business model44s
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Thought exercise: Map your data lifecycle1m 32s
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Thought exercise: Identify your stakeholders1m 12s
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Thought exercise: Evaluate how stakeholders drive revenue41s
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Thought exercise: Assess how DQ impacts revenue and risk48s
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Thought exercise: Synthesize research and communicate ROI3m 15s
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