3.2.Bias, credibility, privacy, ethics, and access - sj50179/Google-Data-Analytics-Professional-Certificate GitHub Wiki

When data analysts work with data, they always check that the data is unbiased and credible. In this part of the course, you’ll learn how to identify different types of bias in data and how to ensure credibility in your data. You’ll also explore open data and the relationship between and importance of data ethics and data privacy.

Learning Objectives

• Explain what is involved in reviewing data to identify bias
• Discuss the difference between biased and unbiased data
• Identify different types of bias including confirmation, interpretation, and observer bias
• Discuss characteristics of credible sources of data including reference to untidy data
• Explain the concept of open data with reference to the ongoing debate in data analytics
• Define data ethics and data privacy
• Explain the relationship between data ethics and data privacy
• Demonstrate an understanding of the benefits of anonymizing data
• Demonstrate an awareness of the accessibility issues associated with open data

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• Unbiased and objective data & Explore data credibility
• Data ethics and privacy & Understanding open data
• Weekly challenge 2