TABLEAU assignment

The purpose of analytics is to apply techniques & tools to the analysis of data to gain insight to make informed decisions in the finance performance/risk area OR marketing consumer confidence index, University of Michigan – choose one!

Due Date: Upload via blackboard link in content by 10/23/17, Monday, 11-59 pm

Penalty per day delay: 10% up to 3 days after which assignment is unacceptable. A minute late is counted as one day late.

INSTRUCTIONS

1. Work on this assignment individually. Penalty for any form of copying or cheating is an “F” grade.

2. Please upload a zipped file [file name: your last name Tableau]. This zipped file consists of the following: Word file (executive summary) + Tableau files. Upload the zipped file via link in Content.

3. Your executive summary is a Word file. It must have a cover page. Number each page in top, right corner. Following the cover page, include a maximum “4-pages,” double-spaced, executive summary. This is followed by readable screenshots of all charts. Each chart must have a proper, relevant title at top (e.g., Figure 1: Heat map of the average eps/stock price for 30 companies, 2012-2014 – RP Raghupathi OR e.g., Figure 1: Correlation between gender and personal finance status, 2002-2014 – RP Raghupathi).

4. Each chart must be on a separate page. Cite the charts (e.g., Figure 1, Figure 2, etc) in your executive summary. Do not put charts in the middle of the executive summary. Put your name in chart titles in Tableau prior to copy/paste into Word; Highlight key values.

5. Use font size: 12 or above.

6. The “4-pages” executive summary should be properly organized and structured: use sub-titles, indenting, paragraphing, etc. DO NOT UNDERLINE OR USE ITALICS. You can ‘bold’ the sub-titles. WRITE IN 3RD PERSON (NOT IN 1ST PERSON – I/WE, OR 2ND PERSON – YOU). Include the following sections - Introduction, Research question/problem statement, Overview of data, Overview of what was done, Discussion of results/outputs in aggregate (at high level), Conclusion(s), Implications, and Recommendations.

7. Please do not use Google Docs – it does not format well in Word.

Analytics – what to do?

1. Do 8 different specific types of analytics (charts) on the data. The 8th analytic should be a dashboard of other key analytics.

2. Use multiple dimensions and factors (variables) in each analytic for robust and rich analytics.

3. Use a variety of features such as dynamic trend analysis, heat map, bubble chart, bullet chart, combination chart, basic statistics, bars, circles, scatter plot, trend line, etc.

4. As you formulate your analytics and choose dimensions (factors/variables), think about causality and correlation among and between the dimensions.

5. There should be a good mix of descriptive and predictive analytics.

6. Our goal is to be ‘data driven.’ Let the data speak for itself.

7. Study the visual charts to gain insight (conclusions).

8. From the insight make recommendations.