This is a Collaborative Learning Community (CLC) assignment.
Now that you have identified the business problem, translated it into an analytics problem, identified the data needs, and acquired the data, you will use data that you have found (or with the company’s permission you can use its data for analysis) to resolve the analytics problem. It is strongly recommended you review “The CRISP-DM User Guide” (Section 3 – Data Preparation), located in the Class Resources, for this phase and supplement with any elements relevant to your subject matter. Using one or more of the following software applications (Excel, PowerBI, Tableau, R, Python, or KNIME), analyze the data so that the findings can be used to address the established business problem in your company.
Conduct an exploratory data analysis and provide a draft outline describing the key features of the data and any significant relationships and information contained in the data set that you found. You are required to include specific screenshots of graphs, tables, etc., that are provided:
How are you going to summarize data samples?
Are there any missing data? Construct data by production of derived attributes, new records, or transformed values for existing attributes. Integrate data by combining information from multiple tables or other information sources to create new records.
Perform any syntactic modifications made to the data format that do not change its meaning but might be required by the modeling tool.
Indicate the steps you have taken to investigate the quality of the data and indicate any variables you have transformed or discarded as a result.
How did you verify that the data were reliable before proceeding?
What problems did you find and how did you address them?
Segment the data accordingly, if needed, to help describe the data behavior. Ensure you still are not violating Simpson’s rule. Did you have to redo your sample? Can you identify any data anomalies? If there are anomalies, what do they represent and how do you avoid them?
Next, you will work on descriptive analytics. Supplement your description with appropriate charts/figures and finalize by creating an appropriate dashboard with Excel, PowerBI, or Tableau. Include a summary that provides a detailed overview of the data behavior you have identified based upon the analysis. Indicate any causal relationships you found.
Provide the raw software files (Excel, PowerBI, Tableau, R, Python, or KNIME ) that you used for this assignment.
Synthesize the information from your draft outline to complete, in 1,500–2,000 words, the relevant components in the Data Diagnostics and Descriptive Summary section of the “Capstone Project Thesis” template.
Submit your draft outline, raw data Excel files, screenshots, and the updated “Capstone Project Thesis” template.
Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
You are required to submit this assignment to LopesWrite. A link to the LopesWrite technical support articles is in Class Resources if you need assistance.
