From the course: Data Quality: Core Concepts

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Data lifecycle stakeholders: Data

Data lifecycle stakeholders: Data

From the course: Data Quality: Core Concepts

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Data lifecycle stakeholders: Data

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- [Instructor] Finally, we have the data stakeholders. One of the first hires for any data org is often a data analyst and where they sit is they take the curated data, often found in an analytical database, and turn it into insights, such as analytics or dashboards. Then we have data scientists who have a very similar role, but with a focus on developing data products. Again, they use the curated data from marts or warehouses where it may be, they do analytics and R&D, such as building machine learning models, and then they help with other engineers to put it into production. One key difference between analysts and data scientists is analysts are often looking back at what happened to the business, while scientists are often looking forward to what they can do with the data. In the next set of slides, we'll move away from stakeholders and start going to the tooling used to support data quality.

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