Data analytics is the process of examining, cleaning, transforming, and interpreting data to discover meaningful insights, patterns, and trends that can inform decision-making and drive business or organizational outcomes. As we begin to explore the various techniques and tools to extract valuable information from large sets of data, whether structured (e.g., databases) or unstructured (e.g., text documents, social media posts), we must also be conscious about the various forms of our own personal bias (i.e. Selections, Sampling, Measurement, Response, Algorithmic, Confirmation, Historical, Ethical, etc.) that may lead to unfair, incomplete, or misleading results and decisions.
For this use your favorite search engine to search for forms of bias in data analytics. Choose at at least one form of bias and and post the following:
- A post must that is at least 200 words.
- Discuss your chosen bias (what it is and how it occurs)
- Potential negative outcomes
- Options to remedy
- At least one example