Review all chapters of the course textbook, Business Analytics: Communicating with Numbers, 2e. Review the infographic Three Types of Analytics Techniques?. Long description This

Data and Decision Analytics Assessment

[WLOs: 1, 2] [CLOs: 1, 2, 3, 4, 5]

Prior to beginning work on this paper

• Review all chapters of the course textbook, Business Analytics: Communicating with Numbers, 2e.
• Review the infographic “Three Types of Analytics Techniques”.

Long description

This final paper is the major summative assignment of this course. It is designed to allow students to reflect on and apply the knowledge of data-based decision-making learned during the course to real-world scenarios.

Assessment Guidelines

For your workbook:

• Respond to the following five (5) questions related to one of the learning objectives covered in this course.
• For each question, confirm your answers with examples of data sets and/or visualizations.
• While you may choose these from the sample data sets provided in the resources listed for this course, It is strongly recommended that you search for new data sources to use as examples.

Questions:

• Differentiate between various types of data an organization may use to assess organizational performance.
  • Provide an example for each data source.
  • Highlight the purpose of the data sources, the metric(s) it explains, and what kind of decision it would help justify.
• Create a data visualization graphic that incorporates appropriate data sets.
  • Consider one of the data sets you have shared in question number 1 of this workbook.
• Evaluate the benefits of at least two different data analysis methods.
  • Share an example of each.
  • Explain how, when, and why these methods have been used in a business situation.
• Justify a strategic choice based on a data analysis method.
  • Use the data analysis method in Week 3 or another example of your choice.
• Assess how big data can influence organizational performance.
  • You may consider using an example if you find that helpful to support your argument.
  • Consider how data can create insight into a business problem and provide a sense of decision-making justification.

The Data and Decision Analytics Assessment paper

• must be five to seven double-spaced pages in length (not including title and references pages, charts or tables), and formatted according to as outlined in the Writing Center’s resource.
• must include a separate title page with the following:
  • title of paper in bold font
    • Space should appear between the title and the rest of the information on the title page.
  • student’s name
  • name of institution (The University of Arizona Global Campus)
  • course name and number
  • instructor’s name
  • due date
• must utilize academic voice. Review the resource for additional guidance.
• must include an introduction and conclusion paragraph.
  • Your introduction paragraph needs to end with a clear thesis statement that indicates the purpose of your paper.
  • For assistance on writing as well as , refer to the Writing Center resources.
• must use at least one credible source in addition to the course text.
  • The table offers additional guidance on appropriate source types.
  • To assist you in completing the research required for this assignment, review tutorial, which introduces the University of Arizona Global Campus.
• While sharing examples for data sets, visualizations, consider referring to one of the recommended websites for this week. These include:
• If you have questions about whether a specific source is appropriate for this assignment, please contact your instructor. Your instructor has the final say about the appropriateness of a specific source for a particular assignment.
• must document any information used from sources in APA Style as outlined in the Writing Center’s guide.
• must include a separate references page that is formatted according to APA Style as outlined in the Writing Center.
  • Review the resource in the Writing Center for specifications.

| Skills Learned

This activity helps you practice the following industry-required skills:

• Data Management
• Graphical Representation
• Data Analysis
• Strategic Decision-Making
• Big Data
• Research Methods
• Market Analysis