1. Course Lab Introduction to IBM Watson Analytics
University of Rome «La Sapienza»
Course of Business Intelligence
Course Lab Introduction to IBM Watson Analytics

2. Ing. Ivonne E. Vereau Tolino
Lab Speakers
Ing. Vittorio Carullo
Software Architect
IBM Watson Squad Senior Member
Ing. Ivonne E. Vereau Tolino
Software Engineer
IBM Software Services Specialist

3. Target & Scope
Familiarize with a «real» software used in large enterprises
Accomplish small but significant use cases in BI arena
Understand the impact of tools over team productivity
Introduce advanced topics like the use of “non structured” information
Lab sessions will be held on Thursday, starting from September 27, 2018 , pm

4. Labs Schedule Presentation of the tool and its basic features
Lab 1: Introduction to Watson Analytics
Understanding and use of the tool features or conducting BI use cases
Lab 2: Working with Data
Lab 3: Analyze and Discover
Lab 4: Predict and take decisions
Lab 5: Report and visualization
Lab 6: Putting all together
Use of the tool for Advanced Analytics
Lab 6: Working with Social Media
Lab 7: Introduction to Content Analytics
Today’s topic is
highlighted!

5. Reference Materials
Explore IBM Watson Analytics library/analytics/watsonanalyticsgallery/ A gallery of use cases with related datasets and supporting data visualizations IBM Knowledge Center utions.wa.doc/welcome.html A technical reference for product features

6. Today’s Contents: Putting all together
Introducing Use Case
Working with two datasets: Data Join
Refine you data
Create Your Discoveries
Create you Display
Present results

7. Introducing
Use Case

8. The scenario

9. Dataset 1: The happiness score
File name: 2017_World_happiness_metrics.xlsx
These data have been produced by asking sampled people in several countries the following question:
"How would you rate your happiness on a scale of 0 to 10 (where 10 is the happiest) ?"
Then people have motivated their answers with some factors like GDP per capita, health life expectancy, freedom conditions and so on

10. Dataset 1 Columns Description
Name
Description
ISO_Code
3-digit code for the exact identification of the country
Country_Name
Name of the country (in English)
Happiness_Score
An average value representing the average value of perceived happiness for population of that country
GDP
The extent to which GDP per capita contributes to the calculation of the score
Family
The extent to which Family contributes to the calculation of the score
Health
The extent to which Life expectancy contributed to the calculation of the score
Freedom
The extent to which Freedom contributed to the calculation of the score
Generosity
The extent to which Generosity contributed to the calculation of the score
Trust_Government_Corruption
The extent to which perception of corruption of the Government contributed to the calculation of the score
Dystopia_Residual
The extent to which Dystopia Residual (unexplained reasons) contributed to the calculation of the score

11. Dataset 2: World Regions
File name: world regions.xlsx
These data contains the list of world countries with the region, sub- region and intermediate region they belong to:
For instance:
Country: Chile
Intermediate-region: South America
Sub-region: latin America & Caribbean
Region: Americas

12. Dataset 2 Columns Description
Name
Description
Country Name
3-Digit code
ISO code of the country
Region
Region the country belongs to
Sub-region
Sub region the country belongs to
Intermediate-region
Intermediate region the country belongs to

13. What you will do today
You have been asked to produce a report with two views where an user can:
Display the world happiness average score with the possibility to navigate through country, sub-region and region levels
Display a predictive model of the happiness, considering for simplicity’s sake three groups:
High happiness
Intermediate happiness
Low happiness
Use the 2 XLS files presented before as work data sets

14. 2. Data Join

15. Why Data Join?
Data join is handy when all data you need does not reside on a single data asset
In order to join data, you need a column «in common» in both data assets
Common columns must represent the same property, even if in different contexts
Column on data set A must contains same values than dataset B (or at least a subset of them)
Column names do not have to be necessarily identical

16. How to join / 1
Load in Refine mode the first data asset in order to display data sheet
Add the second data asset by clicking on the ‘+’ sign near the data set name (above column names) and selecting the one you want to join

17. How to join / 2 Click on the Join tool on left toolbar
Connect the two columns that have to work as «glue»

18. How to join / 3 Check that joined data are displayed in the above part
Save your data asset with a new name
The saved asset will be displayed with a «joined» icon on your Data tab
NOTE: in WA you can yoin only two
data assets at a time

19. Refine Joined Data

20. Tips and tricks/1
You have to produce a report that can be explored at different geographic levels
By joining the two data assets you have been given, you will have full geo information (region, sub-region, etc) for any row
Use the non-ambiguous data column to join!!
Then you have to create a new column in your data asset to enable the geographic drill-down/drill-up

21. Tips and tricks/2
You have to produce a prediction model based on a simplified perception of happiness (three groups: low, medium, high)
Then you have to create a new column in your data asset that make this possible

22. Create Discoveries

23. Tips and tricks/1
You essentially need two discoveries: a descriptive view and a predictive model (e.g spiral)
You can ask questions on your data asset in order to generate automatically the two discoveries
You can create the discoveries in the same discovery set and then save it
When creating your views, remember that you have to display the average happiness score
Since you are dealing with nations, WA could automatically display the Map view. This is obviously OK.

24. Create Display

25. Tips and tricks/1
Choose the display format you prefer and put the two discoveries in it. This will be your report.
You can enhance your display using icons or customizing colors
You can also add filtering to your display in order to give users moer possibilities to see data

26. Now it is up to YOU!
ENJOY!
Discover
Create