1.
AGENDA
Introduction to Tableau
Problem Statement 1
Problem Statement 2
Conclusion
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2.
Introduction
to Tableau
1.
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3.
Introduction to Tableau
s
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4.
From connection to collaboration, Tableau is the most powerful, secure and flexible end-to-end
analytics platform for your data. Designed for the individual; scaled for the enterprise. Tableau is
the only business intelligence platform that turns your data into insights that drive action.
Introduction to Tableau
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Share Insights with
Tableau Server/Online
Analyse with
Tableau Desktop
Prep Data with
Tableau Prep

5.
Problem
Statement 1
2.
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6.
Problem Statement 1: Use Case
“It is the January of 2016 and the CEO of Superstore is looking to bolster business for the upcoming year. The finance
team has noticed that there were profit problems for some inventory categories during 2015.”
1. You have been tasked with figuring out which item(s) have had profit problems multiple years in a row (both net
and year over year), where the problems are happening, and why.
2. You also need to visualize this data so that multiple teams (leadership, sales, finance, marketing, and
manufacturers) can view the results and understand the data quickly.
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7.
Problem Statement 1: Objective
What you must do;
1. Connect to and analyze Superstore’s data sets from 2012-2015
2. Create a variety of views to explore the data while calling out insights along the way
3. Analyze business profits
4. Discover where and why profit loss is happening
5. Summarize the data on a visual dashboard to submit to the company
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8.
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Problem Statement 1: Objective
What you should expect to learn from this exercise;
1. To connect to data using the web data connector
2. To Analyse Data
3. To Visualize Data
4. To join tables in Tableau
5. To run Table Calculations
6. To use Highlighters, Filters, Formatting, Hierarchies, Aggregations, Geocoding
7. Dashboarding & Publishing

9.
Problem
Statement 2
3.
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10.
Problem Statement 2: Use Case
“The purpose of this project is to understand the content and linguistic style of highly persuasive talks. So, we are trying
to use transcripts of TED Talks to find text features that predict persuasive ratings by users?”
Solution;
Step 1: Scrape the transcripts of TED Talks
Step 2: Use NLP to analyze the text through data science models to provide insights
Step 3: Find text categories with statistically significant relationships with User Ratings & Views
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11.
Problem Statement 2: Hypothesis
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A more persuasive, inspiring talk is related not just to WHAT people are saying but HOW they are saying it.
What people are saying:
• Content Words - job, brain, computer
How they are saying it:
• Emotion Words - happy, sad, angry
• Function Words - I, you, we, what

12.
Problem Statement 2: Analysis Methods
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The tech stack consists of the following;
1. Python 3(NumPy, Pandas, Beautiful Soup, Matplotlib)
2. Linguistic Inquiry and Word Count (LIWC)
3. Natural Language Toolkit (NLTK),
4. Scikit-Learn
5. HTML
6. CSS
7. Flask
8. Heroku
9. Tableau

13.
Problem Statement 2: Analysis Methods
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14.
Conclusion4.
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15.
THANK YOU