Description
Question W2
Review the following article: The DIKW Model for Knowledge Management and Data Value Extraction.
Extraction.
Data comes in many different types. It can be quantitative, qualitative, structured, unstructured, semi-structured, or a mix of all of these. Data in its raw form alone is not very helpful in decision making or providing useful information. However, to apply structure to the data also requires a degree of bias when the choice of which data are most appropriate is made.
Using the readings for this week in conjunction with the article presented in this discussion, consider that a healthcare clinic will collect demographic information about patients, as well as information about each patients visit. Quantitative and structured data will be entered in the record system about a patients vitals and medical history, but the physician will also enter qualitative and unstructured information as they describe a patients symptoms or what they are experiencing. What types of questions might be asked that could be applied to the data to inform the organization about the patients? What might the organization do with the data to inform future decisions such as purchasing supplies, medications, equipment, personnel, etc., in order to plan for possible future patients based on the data? What challenges might exist in working with unstructured data?
Question W3
The reading material this week covers the context of how artificial intelligence (AI) and machine learning (ML) influence the capabilities of big data analytics. Address the following in your discussion:
1. Identify and discuss two advantages of machine learning and AI in big data analytics.
2. How has the use of AI and ML impacted businesses such as Amazon, Walmart, or the
travel industry?
Question W4
Data on its own is not very useful or informative, unless you apply organization and structure. Once the data is structured, it can then be used to tell a story or provide information that can be used to inform decisions. What information or story is told depends on many factors, but mostly relies on what you want to know.
Two data sets are provided in this weeks content: Social Climbers.xlsx and Artsy Lawsuit.xslx. Use these data sets to perform the following tasks within the spreadsheets:https://www.tableau.com/learn/articles/free-public…
Social Climbers
– Compare the data to determine where relationships may exist. For example, you may ask if there is a relationship between education and income levels. Perform at least four different data comparisons.
– Provide an explanation based on your comparison results. Where do relationships exist and where do they not exist, according to the data?
Artsy Lawsuit
– The story behind these data comes from a discrimination lawsuit filed, accusing the Artsy
company of improper hiring processes and employment pay between men and women. Your task is to use these data to determine if the plaintiffs have a valid or strong case, which would then be presented in court to a jury.
– Use basic statistical analysis to compare the data.
In both of these data sets, you may choose to use the tools below or any others you feel are appropriate to tell the story and interpret the data. Not all tests are applicable for all data sets. It depends on the types of data and what you want to know:
– Mean, median, mode
– Quartiles
– Pivot tables
– Regression
– T-tests
– Time series
– Graphs, plots
Question W5
The reading this week explores various uses of big data analytics in supply chain management,
such as:
? Sustainability
? Demand planning
? Supply chain network design
? Procurement management
? Product development and design
? Logistics
The speed in which decisions must be made in todays technology-driven world is immense, and businesses are under extreme pressure to find better ways to compete. Tools such as AI, ML, predictive analytics, and prescriptive analytics can help businesses make faster decisions, impacting business operations.
Select an organization operating in supply chainhttps://www.thomasnet.com/insights/the-10-best-sup… or shipping operations https://www.fedex.com/en-us/about/policy/technolog…. Research how they currently use AI, ML, predictive and/or prescriptive analytics. Share your findings and include your resources. How do these tools help the organization manage supply chain resources and product deliveries?
Question W6
Watch the following video:
Using information given in the video, think of a business that may use data to apply predictive analytics to make business operations decisions. Discuss what types of data would need to be collected, how that information would be gathered, and how the relationships between those data would be identified and used. Think of and share how these same concepts may be applied in your current or a past job role.
Question W7
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?
Question W8
This week, you examined several different types of data insights that occur in big data analytics:
? Offer novel knowledge
? Provide causation relationships
? Add a competitive edge
? Yield quantifiable results
? Demand execution
Pick one of the insight pillars above and discuss how it supports overall business strategy. Consider your current or a previous workplace, and address how the insight may apply. What can the business do now to use data to address the insight you have selected?
