To make sense of all the data available to them, business leaders work alongside data scientists who generate data visualizations to understand business questions via analytics. This process gives companies insight on what is working and what is not: for example, whether the products or services offered are meeting expectations, or if a shift in strategy is necessary.
For this assignment, you will take on the role of a business leader who wishes to analyze if a new product their company has introduced is meeting the expectations. Imagine that you would like to create a post in the company intranet that summarizes your findings in an easy-to-read format for your team. Pay special attention to creating meaningful data visualizations. You should use techniques that make content easy to follow but that also display charts accurately without distorting or skewing data. Your company’s profit goal is 25% of the cost of goods sold (COGS). Remember, COGS is the cost of manufacturing the product, including labor, materials, and overhead. You will need to build trust and an open channel of communication with other leaders on your team. Pay close attention to the story that data visualizations tell you and others reviewing your post.
The purpose of this analysis is to better understand the cost, revenue, and profit associated with the new product launch. Review the Cost, Revenue, and Profit Spreadsheet retrieved from the company’s data center and consider the following while developing your ideas in this assignment.
What is the importance of data analysis?
What are the results of your analysis?
Think about your analysis and its findings, including visuals. Use visuals and text to re-state the purpose of your analysis and summarize your most important findings.
What are you trying to represent with this data?
What kind of graphic have you selected and why?
How did adding visual representations of the data change your analysis?
Does the target audience influence the way you display information?
Guidelines for Submission
Complete the Making Data Driven Decisions worksheet in your Soomo webtext, download your completed work, and submit it in Brightspace for instructor feedback. You should write using a professional voice, and any sources should be cited according to APA style. Your assignment must be between 400 and 800 words in length.
Module Four Assignment Rubric
Criteria Exemplary (100%) Proficient (85%) Needs Improvement (55%) Not Evident (0%) Value
Analysis Exceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative manner Determines importance of data analysis Shows progress toward proficiency, but with errors or omissions; areas for improvement may include statement on the importance of data analysis Does not attempt criterion 25
Findings Exceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative manner Describes results of the analysis Shows progress toward proficiency, but with errors or omissions; areas for improvement may include incomplete or inaccurate description of the results of the analysis Does not attempt criterion 25
Summary Exceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative manner Describes analysis and its findings using text and visual representations Shows progress toward proficiency, but with errors or omissions; areas for improvement may include incomplete or inaccurate description of the analysis and its findings Does not attempt criterion 30
Articulation of Response Exceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative manner Clearly conveys meaning with correct grammar, sentence structure, and spelling, demonstrating an understanding of audience and purpose Shows progress toward proficiency, but with errors in grammar, sentence structure, and spelling, negatively impacting readability Submission has critical errors in grammar, sentence structure, and spelling, preventing understanding of ideas 10
Citations and Attributions Uses citations for ideas requiring attribution, with few or no minor errors Uses citations for ideas requiring attribution, with consistent minor errors Uses citations for ideas requiring attribution, with major errors Does not use citations for ideas requiring attribution 10
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