代做Business information systems (MISY261)代做留学生SQL语言

Data analysis report

Course: Business information systems (MISY261)

Background and Purpose:

This section describes any information needed to provide the reader with an understanding of the background for the analysis and its purpose. First, you should address where the dataset originated, an overview of the data, and who the target audience will be for this analysis (specific industry, client, organization, etc.).

Next, describe the purpose(s) of the analysis in a business context. Your analysis purpose and questions below MUST be business-related and seek to answer questions that would help an industry/organization/client because of your work. You need to have at least one purpose, but you may also have more than one purpose to align with your research questions. It is recommended that you write this section at the same time you are determining the research questions, so they are cohesive.

Data Dictionary:

Use the table below to create your Data Dictionary. Feel free to add additional rows if you have a larger dataset or take out rows if you have a shorter dataset. Data types should be either Integer, String, Double, or Date/Time).

Column Name	Description	Data Type	Sample Values

Research Questions and Reasoning:

A key element of an effective analysis is careful specification of the questions to be addressed BEFORE starting the analysis.  The clearer and more detailed these questions are, the more likely that you will be able to provide useful answers to them. Each question must be formulated as a question, and each question defense must be a paragraph in length.

1. Research Question 1:

Question Defense:

2. Research Question 2:

Question Defense:

3. Research Question 3:

Question Defense:

Data Cleaning Summary:

After determining the research questions, your next step is to prepare the data for creating visuals. During the data cleaning process, you may need to eliminate useless data, reformat data, create flag variables, remove duplicates or outliers, replace missing data, or complete other tasks. This section should mention at least four cleaning tasks you completed and explain why each task was necessary. If you created flag variables, also copy and paste your formulas/functions in this section.

Dashboard:

This section should only contain a screenshot of your completed dashboard from Tableau (or you can screenshot each individual visualization if easier to read). Before creating your visuals, make sure to import your cleaned dataset into Tableau. Begin by creating worksheets for each visual. Your visuals should be diverse and not be consistently one type of visual (for example, all your visualizations should not be column charts). Also, visuals should include proper chart titles that accurately describe the visual, axis titles, a consistent color palette, and legends (where appropriate). Furthermore, each visualization must serve the purpose of answering a research question. Lastly, your visuals must look professional and clean. If your visual is returning a lot of data, consider using the Top 10 of what you are trying to answer.

Under the dashboard (or each visualization) explain in 3 to 5 sentences (per visualization) which preattentive attributes and/or Gestalt principles were applied to each visualization to decrease the cognitive load of the reader.

Results and Recommendations:

This section spells out the findings of your analysis and directly answers each of your three research questions. What would you recommend to your chosen industry/organization/client based on the results? What additional takeaways did you identify outside of your research questions?