Data Science e Industry 4.0: rivoluzioni culturali rese possibili dalla tecnologia

1. I N V E S T I N G O N D ATA
The future is going to be data driven

2. Luigi Roggia - www.applyscience.it
I N T R O D U C T I O N

3. Luigi Roggia - www.applyscience.it
• Master’s Degree in Physics
• Master in Bioinformatics
• Founder of Data Science
companies
• 18 years experience in applied
mathematics
• Lead data scientist for
international enterprises
A B O U T M E

4. Luigi Roggia - www.applyscience.it
A P P LY S C I E N C E
Apply Science is a scientific company dedicated to the application of
mathematical methods and models to business use cases.
Main Division
Life Science Division
Quantum Division
0 25 50 75 100
90
10
10
5
70
20
5
20
70
Consultancy Products Research

5. Luigi Roggia - www.applyscience.it
I N V E S T I N G O N D ATA

6. I N V E S T I N G O N D ATA I S
A C U LT U R A L
R E V O L U T I O N M A D E
P O S S I B L E B Y
T E C H N O L O G Y
D ATA S C I E N C E A N D I N D U S T RY 4 . 0
A R E T H E M A I N K E Y W O R D S O F T H I S R E V O L U T I O N
Luigi Roggia - www.applyscience.it

7. W H AT A R E W E TA L K I N G
A B O U T ?
These words on the right are more
and more used associated with the
most modern business trends.
All these concepts are different
aspects of a unique main aim:
Investing on data
I N T E R N E T O F T H I N G S
B I G D ATA A N A LY S I S
I N D U S T RY 4 . 0
D ATA S C I E N C E
Luigi Roggia - www.applyscience.it

8. D ATA A L C H E M Y
D ATA
I N F O R M AT I O N
K N O W L E D G E
D E C I S I O N
Data alone is just potential
energy.
Mathematics can extract
information from data.
Information leads to
knowledge.
Knowledge then is used to
take decisions.
This is being data driven!
Luigi Roggia - www.applyscience.it

9. Luigi Roggia - www.applyscience.it
D ATA S C I E N C E

10. D ATA S C I E N C E
Data Science is the science and
art of turning data into
revenues.
Basically the idea behind Data
Science is that when
complimentary skills are put
together into a team, the output
is much greater than the sum of
the separated values.
Data Science is always business
oriented.
Luigi Roggia - www.applyscience.it

11. T H E 3 L AY E R S O F D ATA
S C I E N C E
Experience shows that for a
successful implementation of Data
Science, three hierarchic layers have
to be defined.
Each layer is important.
Specific skills are required according
to each layer.
D ATA L A K E
W H E R E D ATA I S C O L L E C T E D , VA L I D AT E D A N D
P R E PA R E D F O R A N A LY S I S
S C I E N C E
W H E R E D ATA S C I E N T I S T S D O T H E I R M A G I C
W I T H M AT H A N D S TAT
U S A B I L I T Y
W H E R E R E S U LT S A R E M A D E AVA I L A B L E A N D
U S A B L E F O R B U S I N E S S
1
2
3
Luigi Roggia - www.applyscience.it

12. Luigi Roggia - www.applyscience.it
I N D U S T RY 4 . 0

13. I N D U S T RY 4 . 0
Luigi Roggia - www.applyscience.it

14. I N D U S T RY 4 . 0 & D ATA S C I E N C E
These are the
3 layers of
Data Science
Luigi Roggia - www.applyscience.it

15. Luigi Roggia - www.applyscience.it
B I G D ATA

16. A N D W H AT A B O U T B I G D ATA ?
What does big actually mean?
Maybe data is big when it cannot be managed on a single machine?
The answer is that it is big data when big data technology is
required.
Luigi Roggia - www.applyscience.it
Big data technology
means solutions based on
Hadoop/Spark.

17. I S M Y D ATA B I G ?
Good question!
Often much more data
than needed is collected.
Yet it is only through Data
Science that we can
understand the real
amount of data required
to solve a given problem.
Luigi Roggia - www.applyscience.it
Consolidating
Requirements
Architecture
Assessment
Technology
Evaluation
Prototyping
Solution
Development
Deployment
Go Live with
Data

18. B I G D ATA C H A L L E N G E S
Luigi Roggia - www.applyscience.it
Basically there are two main
challenges:
• Technology itself
• The nature of big data

19. Luigi Roggia - www.applyscience.it
W E A P O N S

20. M A I N T O O L S
Luigi Roggia - www.applyscience.it
Programming languages are the main tools
that any (true) data scientist loves and has
to use.
The two most widely used languages are R
and Python.
• Statistics
• Machine learning
• Data wrangling
• Data exploration
• Mathematical models
• Scientific models

21. I N D U S T R I A L S TAT I S T I C S
Luigi Roggia - www.applyscience.it
Minitab is the leading software for quality
Statistics and process optimisation:
• Capability analysis
• Analysis of variance
• Design of experiment
• Control charts
• Reliability analysis
A must have in manufacturing!

22. M A K I N G I T U S A B L E
Luigi Roggia - www.applyscience.it
Making a good data product is a hard job…
To get it simple, scalable and highly
performant we use TIBCO technology:
• Easy, modular, scalable
• R & Python integration
• Real time analysis
• Big data analysis
• Cloud dashboards

23. T H E W H O L E P I C T U R E
Luigi Roggia - www.applyscience.it
D ATA L A K E
M I N I TA B R / P Y T H O N T I B C O
Industrial statistics has a full great implementation in Minitab. R/Python can scale
models to real time and big data, that find an enterprise level deployment with TIBCO
M L L I B SR E P O RT R E P O RT

24. T H A N K Y O U !
Luigi Roggia
CEO & data scientist @ Apply Science
www.applyscience.it
info@applyscience.it
Luigi Roggia - www.applyscience.it