This document provides an overview of a visual analytics course using Tableau. The course structure includes modules on Tableau Desktop foundations, exploratory data analysis, creating analytics dashboards, advanced predictive analytics with R programming, and completing visual analytics projects. Learners will gain skills in exploratory data analytics, building dashboards, predictive analytics, and developing a project portfolio. Case studies will cover topics like geo-data analysis, customer segmentation, and price index analysis. The importance of visual analytics and Tableau for industries like sales, marketing, and finance is also discussed.
2. Speaker
Program Director Industry Analytics Bootcamps,
UpX Academy
MSc, Molecular Cell Biology, University of Cologne
MBA, Darmstadt University
Arun Reddy K
01
8. 02
How did the Tableau journey start?
Product Leader
in self service
analytics
2016 - Present
Created by an founder of Pixar &
a brilliant computer scientist at
Stanford university
Recorded an
82% user
growth
2002 2008 2013
Desktop version 4
released
Image source: Proprietary logos
9. To help people visualize and understand data
Vision of Tableau
18. 04
Tableau Ecosystem - Products
There are two desktop
versions of Tableau we
would explore
• Tableau Desktop enterprise
• Tableau Public version
Image source: Tableau software
23. • Your current goal is to increase your
revenue by 20% YOY till 2020
• You want to decide which markets
should you focus on for growth
• & understand your competitors pricing
strategy in various markets
24. 09
• Discuss with your Business development
team, on execution strategy, but we need
data first to gain more insights
• Analytics team has to prepare a report
to analyse the revenue trends for each
country around the world
• & identify hot tourism and travel markets
all over the world
• Need to analyse previous years revenue
trends as well and project figures for next
two years
Next Steps
28. The challenges faced by the analytics team?
Gather data
Analyse data
Present data: through visuals to the CEO
29. Gathering relevant data is a challenge
09
• Country tourism data from
government websites
• Past data from hotel bookings
• Competitors data through web
scraping
• External market research data
30. Perform relevant analysis suitable for the problem
09
• Understand business objective
• Examine past data
• Identify trends
• Summarize
• Predict future trends
• Identify Travel hotspots
Analyse data
31. 09
How do Data scientists address this challenge?
Breakdown your
analysis
32. 09
How do Data scientists address this challenge?
Focus your analysis
on each market
Using dashboards
33. 09
How do Data scientists address this challenge?
Present the
High level Information
to the CEO
39. 07
“if you first explore and understand
the data using visualization
techniques, your work will go much
faster”
A Data scientist
Reference: https://www.quora.com/What-are-the-most-common-mistakes-made-by-aspiring-data-scientists
How does visual analytics help?
47. Understanding Stakeholders needs is most crucial!
11
• Improve operational efficiency
• Implement quick solutions
• Execute a turnaround
Clients!
48. Understanding Stakeholders needs is most crucial!
11
• More strategic thought oriented
• Calculate longer term prospects
• Focus on growth
• Prepare for uncertainties in business
Executives
49. Understanding Stakeholders needs is most crucial!
11
• Problem solving approach
• More process oriented
• Define multiple solutions
• What if scenario analysis
Managers
50. • Allows understand data quickly
• Discover hidden facts
• Storytelling & Reporting insights to various stakeholders
• Make relevant and timely data driven Business decisions
10
Summarizing visual analytics introduction
52. Some of the Images
used in the
preparation of this
deck are collected
using Google image
search for the
purpose of
education. We hold
no copyrights for the
images used