Assignment 6-A

Create a Tableau Story and Dashboards

Translate data into a polished Tableau story that communicates a clear narrative with interactive dashboards and actionable recommendations.

3-4 hours
Intermediate
100 Points
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What You'll Practice
  • Designing dashboards with a narrative flow
  • Using Tableau story points and filters
  • Publishing and sharing interactive work
  • Translating insights into recommendations
  • Effective data visualization choices
Contents
01

Assignment Overview

In this assignment you will design a multi-slide Tableau story that guides a stakeholder through a clear data narrative. You will translate raw sales data into a concise sequence of dashboards that support decision-making. Focus on clarity: each story point should answer one specific question and lead to a recommendation. Deliver a published workbook or a packaged file plus a README that documents how to view and interpret your story.

Deliverables

Packaged workbook (.twbx) or Tableau Public link, dataset, README

Story Points

3-5 slides that form a coherent narrative (overview, drivers, recommendations)

Publish

Publish to Tableau Public or include a downloadable workbook with screenshots

Skills Applied: dashboard design, data preparation for visualization, storyboarding, and sharing interactive work.
Quick Data Prep Examples (Python)
import pandas as pd

# Example 1: Aggregate daily sales to monthly totals
df = pd.read_csv('sales_data.csv', parse_dates=['date'])
monthly = df.set_index('date').resample('M').agg({'revenue':'sum','units_sold':'sum'}).reset_index()
print(monthly.head())  # Shows first 5 months with totals
# Example 2: Prepare category-level summary for Tableau
cat_summary = df.groupby(['region','category']).agg(total_revenue=('revenue','sum'),
                                                   avg_price=('revenue','sum')/('units_sold','sum'))
cat_summary = cat_summary.reset_index()
# Save cleansed file for Tableau
cat_summary.to_csv('sales_by_region_category.csv', index=False)  # Ready to load in Tableau

Practice Questions: Data Prep

Load the CSV and compute which month has the highest revenue.

Solution 
import pandas as pd

df = pd.read_csv('sales_data.csv', parse_dates=['date'])
monthly = df.set_index('date').resample('M').agg({'revenue':'sum'}).reset_index()
peak = monthly.loc[monthly['revenue'].idxmax()]
print(peak)  # e.g., 2025-07-31 with revenue 12345.67

Compute percent contribution of each region to total revenue and save for Tableau.

Solution 
import pandas as pd

df = pd.read_csv('sales_data.csv')
region = df.groupby('region').agg(total_revenue=('revenue','sum')).reset_index()
region['pct'] = region['total_revenue'] / region['total_revenue'].sum() * 100
region.to_csv('region_contribution.csv', index=False)
print(region.sort_values('pct', ascending=False).head())
CSV Previewer (Interactive)

Choose a local CSV to preview the first 10 rows before importing into Tableau.

Quick Checklist: Ensure dataset is cleaned, story has 3-5 points, dashboards labeled, and README includes link or workbook.
Submit Assignment
02

The Scenario

Retail Insights Co.

You are a data analyst at Retail Insights Co. A client sells appliances across multiple regions and wants a Tableau story that explains sales trends, seasonality, and regional performance so they can prioritize inventory and promotions.

"We need a concise dashboard story to take to the executive meeting. Show us where sales are growing or declining and where to focus marketing."

Your Task

Build a Tableau workbook with multiple dashboards and a story. Publish it to Tableau Public or provide a downloadable workbook and include a short embed or screenshots in your README.

03

The Dataset

Use the provided sales dataset or a similar public dataset. Save it as sales_data.csv in your project repository. The dataset includes sales by date, region, product category, units, and revenue.

Dataset Columns
  • date - Transaction date
  • region - Region name
  • category - Product category
  • units_sold - Units sold
  • revenue - Revenue in USD
04

Requirements

Your submission must meet the items below. Focus on clarity, story flow, and interactivity.

1
Story Overview (Text)

A short executive summary and the main question your story answers.

2
Dashboards (Tableau)

At least two dashboards: an overview and a deep dive with filters. Use well chosen chart types and labels.

3
Story Points

Create a sequence of story points (3-5) that guide the viewer through insights and decisions.

4
Publish or Export

Publish to Tableau Public or provide the packaged workbook and include links or screenshots in the README.

5
README and Presentation

Include README with summary, dataset description, instructions to view, and a brief presentation or explanation of your story.

Pro Tip: Focus on the narrative and how each dashboard supports a decision. Keep visuals simple and labeled.
05

Submission

Create a public GitHub repository named tableau-story-<your-username>, include the workbook or link to Tableau Public and add the required files listed below.

Required Repository Name
tableau-story-<your-username>
github.com/<your-username>/tableau-story-<your-username>
Required Files
tableau-story-/
├── sales_data.csv        # The dataset or link to dataset
├── workbook.twbx         # Tableau packaged workbook OR a link to Tableau Public in README
├── README.md             # REQUIRED - see contents below
└── screenshots/          # Optional - images demonstrating story points
README.md Must Include:
  • Your full name and submission date
  • Brief description of the story flow and how to view the workbook
  • Link to Tableau Public (if published) or instructions to open the workbook
  • Key findings and recommended next steps
Do Include
  • Clear story flow and labelled dashboards
  • Published workbook or packaged workbook file
  • README with link and instructions
  • Short executive summary and recommendations
Do Not Include
  • Private links that cannot be accessed
  • Excessively cluttered dashboards
  • Unexplained filters or unclear labels
Important: If you publish to Tableau Public, ensure the workbook is visible and the link is included in the README.
Submit Your Assignment
06

Grading Rubric

Your assignment will be graded on the following criteria:

Criteria Points Description
Story & Narrative 25 Clear flow of story points and decision-oriented narrative
Visual Design 20 Appropriate charts, labels, and clean layout
Interactivity 20 Filters, highlights, and working actions that aid exploration
Findings & Recommendations 20 Actionable recommendations backed by analysis
Documentation 15 README and presentation clarity
Total 100
07

What You Will Practice

Storytelling with Data

Create a narrative that connects charts to decisions

Dashboard Design

Compose clear overview and deep dive dashboards

Publishing

Share interactive work and include viewing instructions

Insight Communication

Translate analysis into short, actionable recommendations

08

Pro Tips

Getting Started
  • Sketch your story on paper before building it
  • Decide which charts best answer your questions
  • Keep visuals uncluttered and labelled
  • Test filters and interactions
Documentation
  • Include a short presentation outline in README
  • Describe each dashboard and its point
  • Provide link to Tableau Public or packaged workbook
  • Include screenshots for clarity
09

Pre-Submission Checklist

Workbook Requirements
Repository Requirements