Data Privacy
Data privacy can be a huge issue for data analysts to understand in order to work effectively. Compliance with data privacy regulations can be seen as both a moving-target-challenge, and as an opportunity.Data privacy standards and regulations can vary widely between business sectors (e.g. U.S. health care’s HIPAA regs) and political jurisdictions (e.g. Germany’s data privacy laws).Please start by reading this article on how some of the users’ anonymized data provided in the Netflix prize dataset was deanonymized:https://www.schneier.com/blog/archives/2007/12/anonymity_and_t_2.htmlThen provide your own curated example that describes a specific data privacy-related issue. In your post, you should provide the link, summarize the article, and discuss the impact of the data privacy information described therein on ongoing data analysis efforts. Changing web IPsPlease download and read:Facebooks Restrictions on User Data Cast a Long Shadow, Deepa Seetharaman and Elizabeth Dwoskin, Wall Street Journal, https://www.dropbox.com/s/mssls6pdsz9gi74/Facebook%E2%8%99s%20Restrictions%20on%20User%20Data%20Cast%20a%20Long%20Shadow%20-%20WSJ.pdf?dl=0, Sep 21, 2015. A considerable amount of the material on the most popular APIs from Facebook, LinkedIn, and other “social media” sites has been either removed or deprecated. New sources of APIs are also constantly emerging. Give an example of where access to web-based data has changed (increased or decreased) over time, whether due to changes in corporate objectives or in the regulatory environment. Who was impacted (positively or negatively) by these changes? What implications if any are there from the standpoint of being able to use this data in downstream analysis and/or product development?
