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Big Data Analytics for Marketing Intelligence Discussion

Big Data Analytics for Marketing Intelligence Discussion



Chapter 12: Big Data Analytics for Marketing Intelligence (p. 215-230)


TEDx Talks. (2019, February 1). The dark side of our personal marketing data – Kirk Grogan – TEDxSeattle [Video]. YouTube.

Alex The Analyst. (2021, September 21). Tableau tutorial for beginners – Installing Tableau – Building first visualization – Part 1/5 [Video]. YouTube.

  • Question1: Discussion 

The reading and videos for this week bring to light some of the ethical and business-related issues in collecting and using data gathered about customer behaviors and using it to target advertising. These data often include things such as location tracking, travel patterns, purchase histories, browsing histories, etc. What are your views regarding the collection of these data about you personally? Do you feel this is a justified and valid business practice? Or do you feel it is an invasion of privacy? These data are gathered through devices such as mobile phones, watches, and other Internet of Things (IoT) technologies. Do you take any actions on your personal devices to manage or limit tracking or protect your privacy by preventing such data gathering?

Question2: Assessment 

  • Big data in the form of immense data sets are not helpful in decision-making without some form of visualization. A picture is worth a thousand words,” definitely rings true in this case. Go to the Free Public Data Sets for Analysis website (…). Select any data set that is of interest to you and download it. The data set should be saved in .CSV format. Scroll to the bottom of the web page and sign up for a free trial of Tableau. If you are not familiar with Tableau, use the video to get a basic introduction so you can apply the concepts to the data set you have downloaded. Use the data set you have selected and create a visualization of the data that can be used to interpret what the data says. Submit your visualization in the form of screenshots and upload them to the assignment area. Grading will be based on your overall application of the data visualization.  

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