Chapter: 3
- How do you describe the importance of data in analytics? Can we think of analytics without data? Explain.
- Considering the new and broad definition of business analytics, what are the main inputs and outputs to the analytics continuum?
- Where do the data for business analytics come from? What are the sources and the nature of those incoming data?
- What are the most common metrics that make for analytics-ready data?
- Go to data.gov. Pick a topic that you are most passionate about. Go through the topic-specific information and explanation provided on the site. Explore the possibilities of downloading the data, and use your favorite data visualization tool to create your own meaningful information and visualizations.
Chapter: 4
- Define data mining. Why are there many names and definitions for data mining?
- What are the main reasons for the recent popularity of data mining?
- Discuss what an organization should consider before making a decision to purchase data mining software.
- Distinguish data mining from other analytical tools and techniques.
- What are the most common metrics that make for analytics-ready data?
- Visit teradatauniversitynetwork.com. Identify case studies and white papers about data mining. Describe recent developments in the field of data mining and predictive modeling.
Alternate link if the link does not work: https://www.teradata.com/University/Academics
When submitting work, be sure to include an APA 7 cover page and include at least two APA formatted references (and APA in-text citations) to support the work this week.
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