This document outlines a 7 step process for creating data visualizations in Tableau. It includes an agenda, descriptions of each step, and demos. The 7 steps are: 1) Connecting to data, 2) Cleaning and preparing data, 3) Creating initial visualizations using Show Me or drag and drop, 4) Editing visualizations, 5) Analyzing data and creating additional visualizations, 6) Creating interactive dashboards, and 7) Sharing visualizations. The presenter leads attendees through examples on air pollution data and life expectancy data to demonstrate the process.

1. DataVisualisation & Analytics with
MARIA KOUMANDRAKI

2. Welcome
BeginnersTableauWorkshop

3. Mission
Learn
Create Have fun
Play Takeaways

4. About me
Maria Koumandraki
• From Chania, Crete, Greece
• Studies-Work: UK, Belgium, Greece
• Campaign Manager @ GTB

5. Agenda
7 steps to create data visualisations with
Tableau
Step 1: Connect with the data
Step 2: Data Cleaning & Prep
Step 3: CreateVisualisations
Step 4: Edit/Format your vizzes
Step 5: Answer advanced questions
Step 6: Interactive Dashboards
Step 7: SharingVisualisations
 Hands-on: Exercises
 Questions

6. Data Analytics using Tableau in 7 steps
Step 1
Connect to the data
Step 3
Use show me to get the
viz
OR
drag and drop in the
row / column shelves
Step 5
Create more vizzes to
get more insights from
the data
Step 7
Save your viz on
Tableau Desktop
OR
share it with
Tableau Server
Step 2
Data Cleaning & Prep:
Rename fields, change
data type, hide, add
new fields etc.
Step 4
Edit your viz
(colours, labels, names,
sort, group, add data
labels, name your
worksheet, filter …)
Step 6
Create a dashboard to
show your findings

7. Let’s get started
Topic: Air Pollution
Data file: csv
Context: Air pollution consists of many pollutants, among other particulate
matter.These particles are able to penetrate deeply into the respiratory tract
and constitute a risk for health.
Pm10: Annual mean concentration of particulate matter
of less than 10 microns of diameter [PM10, ug/m3]
Period: 2008-2015
Coverage: 10 regions, 104 countries, 2,961 cities
Collection:World Health Organisation
Available: Public
Source: http://apps.who.int/gho/data/node.main.152?lang=en

8. Step 1: Connect to the data
Flat files (excel, text, csv)
Relational databases (e.g. SQL
Server)
Online data sources (Adobe, Google
analytics)
And many others (olap cubes)
Choose to connect to:
• New data
• Saved data sources/connections
• Recently opened workbooks

9. DEMO #1

10. Takeaways
STEP 1: Connect to the data

11. Step 2: Data Cleaning & Prep
Rename the data connection
Hide field(s)
Rename field(s)
Change the data type
Assign a geographical role to a field
Edit aliases
Split a field (that has different parts into
separate variables)
Create hierarchies for drill down
Create folders
Group fields
Create extra fields
Use the data interpreter
Pivot

12. DataTypes: Dimensions & Measures
Tableau supports the following data types
Dimensions:Categorical data fields such as gender, product category.
These are fields we want to slice and dice the numerical data by.
Measures: Numerical, continuous data.
The numbers we want to analyse, the metrics.
Date: discrete or continuous
Date & time values
Geographical data (longiture, latitude used for maps)
Boolean values (true/false conditions)

13. DEMO #2

14. Takeaways
STEP 2: Data Cleaning & Prep
20 fields
7 fields

15. Step 3: Create your first viz
You don’t know how you can best visualise the data
Tableau provides a simple tool called “Show Me”
"Show Me" contains a list of common chart types that can help
you start your analysis
Select different dimensions and measures while holding down
the Control key
If you know how you want to view the data
Simply drag & drop fields from the data
window into the canvas directly, or onto the
Columns and row shelf
Or type into the Columns or Rows shelf if you
know the name of the field you want to use

16. DEMO #3

17. Takeaways
STEP 3: Ask questions & create your first viz
Show Me
Drag & Drop

18. Step 4: Edit the viz
Colours
Data labels
Sort
Format
Edit aliases
So much more

19. DEMO #4

20. Takeaways
STEP 4: Edit your vizzes

21. Step 5: Analyze data & get more insights
Ask more questions and create more vizzes
InTableau you can create: maps, bar charts, tree maps, area charts,
bubble charts, line charts, heat maps, histograms, etc.

22. DEMO #5

23. Takeaways
STEP 5: Create advanced visuals

24. Step 6: Create an Interactive Dashboard
To share your findings with your team and/or Manager

25. DEMO #6

26. Takeaways
STEP 6: Create Dashboard

27. Step 7: Share your vizzes & findings
Workbooks can be shared in any
number of ways
Most effective way to share a
workbook is to publish it withTableau
Server orTableau online
Published workbooks are up-to-date,
secure, fully interactive, and viewable
by web browser or on a mobile device
Tableau Reader can view and interact
with workbooks
.
.
.

28. DEMO #7

29. Takeaways
STEP 7: Save your viz and share it

30. Spread sheet Visual
Interactive-dynamic
visualisations
Fast & easy to create & update
The journey

31. Your turn…
Topic: Life Expectancy
Data file: csv
Description: Life expectancy at birth & age 60 (avg. no years)
Period: 2000-2015
Coverage: 6 regions and 194 countries
Collection: World Health Organisation
Available: Public
Source: http://apps.who.int/gho/data/view.main.SDG2016LEXv?lang=en

32. Want to learn more?
Check out the free sources
http://onlinehelp.tableau.com/
https://www.tableau.com/learn/starter-kits
http://onlinehelp.tableau.com/current/guides/get-started-
tutorial/en-us/get-started-tutorial-explore.html
Tableau Public: https://public.tableau.com/s/

33. THANKYOU!