Share any experience involving “dirty data†from your personal or working environment. (If you cannot identify one, provide a hypothetical situation.) Give a reasonable explanation for it and how it could have been prevented. Discuss how data pre-processing would address this issue. Be sure to relate your discussion with the textbook readings in order to get full credit.
Post your answer as a response to this topic, using an appropriate title. When you finished posting, respond to at least one of your colleagues’ responses. This reply should also be 100 words long. You are encouraged also to argue against others’ ideas, but always give reasons, try to keep a friendly, professional, and interested atmosphere. If you are asked a follow-up question, you must respond. Excellent performance will consist of several messages that engage the arguments and ideas being presented, as though you are having an ongoing conversation. (Your original response is worth 1 point and your initial response to another student’s posting and interaction is also worth 1 point.)
Malley, B., Ramazzotti, D., & Tzung-yu, J. (2016). Data Pre-processing. SpringerLink. Retrieved from https://link.springer.com/chapter/10.1007/978-3-319-43742-2_12
Share any experience involving “dirty data†from your personal or working environment. (If you cannot identify one, provide a hypothetical situation.) Give a reasonable explanation for it and how it could have been prevented. Discuss how data pre-processing would address this issue. Be sure to relate your discussion with the textbook readings in order to get full credit.
Post your answer as a response to this topic, using an appropriate title. When you finished posting, respond to at least one of your colleagues’ responses. This reply should also be 100 words long. You are encouraged also to argue against others’ ideas, but always give reasons, try to keep a friendly, professional, and interested atmosphere. If you are asked a follow-up question, you must respond. Excellent performance will consist of several messages that engage the arguments and ideas being presented, as though you are having an ongoing conversation. (Your original response is worth 1 point and your initial response to another student’s posting and interaction is also worth 1 point.)
Malley, B., Ramazzotti, D., & Tzung-yu, J. (2016). Data Pre-processing. SpringerLink. Retrieved from https://link.springer.com/chapter/10.1007/978-3-319-43742-2_12
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