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Tableau Tutorial for Data Science | Edureka

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Tableau Tutorial for Data Science | Edureka

YouTube Link:https://youtu.be/ZHNdSKMluI0
Edureka Tableau Certification Training: https://www.edureka.co/tableau-certification-training
This Edureka's PPT on "Tableau for Data Science" will help you to utilize Tableau as a tool for Data Science, not only for engagement but also comprehension efficiency. Through this PPT, you will learn to gain the maximum amount of insight with the least amount of effort.

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YouTube Link:https://youtu.be/ZHNdSKMluI0
Edureka Tableau Certification Training: https://www.edureka.co/tableau-certification-training
This Edureka's PPT on "Tableau for Data Science" will help you to utilize Tableau as a tool for Data Science, not only for engagement but also comprehension efficiency. Through this PPT, you will learn to gain the maximum amount of insight with the least amount of effort.

Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in

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Tableau Tutorial for Data Science | Edureka

  1. 1. AGENDA Introduction to Tableau Problem Statement 1 Problem Statement 2 Conclusion www.edureka.co
  2. 2. Introduction to Tableau 1. www.edureka.co
  3. 3. Introduction to Tableau s www.edureka.co
  4. 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 www.edureka.co Share Insights with Tableau Server/Online Analyse with Tableau Desktop Prep Data with Tableau Prep
  5. 5. Problem Statement 1 2. www.edureka.co
  6. 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. www.edureka.co
  7. 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 www.edureka.co
  8. 8. www.edureka.co 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. 9. Problem Statement 2 3. www.edureka.co
  10. 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 www.edureka.co
  11. 11. Problem Statement 2: Hypothesis www.edureka.co 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. 12. Problem Statement 2: Analysis Methods www.edureka.co 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. 13. Problem Statement 2: Analysis Methods www.edureka.co
  14. 14. Conclusion4. www.edureka.co
  15. 15. THANK YOU

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