1.
Definition and ensuring of
digital roles and competences
with focus on Big Data
Rocco Defina
September 17th 2020

2.
THE PERSPECTIVE I BRING
A VERY SHORT INTRODUCTION
2
The European effort to foster the IT
Professionalism
– Standardization
(CEN/TC 428 - ICT Professionalism
and Digital Competences)
– IT Role profiles
(Including Data Scientist and Data
Expert)
The effort to bring the results from
research to the market
– Digital Transformation

3.
IMPORTANCE OF COMPETENCES
IMPORTANCE OF CERTIFICATION
IMPORTANCE OF BIG DATA
TABOO WORD: «IMPORTANCE»
3

4.
A STARTING POINT
FROM HTTPS://WWW.ISO.ORG/CERTIFICATION.HTML
4
Certification – the provision by an independent body of
written assurance (a certificate) that the product, service or
system in question meets specific requirements.
Professional certification is the process by which a person
proves that he or she has the knowledge, experience and
skills to perform a specific job and its tasks

5.
THE OTHER INGREDIENTS OF THE RECIPE
5
SPECIFIC
REQUIREMENTS
TRAINING
ASSESSMENT
CERTIFICATION
- Roles
- Competences
KEY ASPECTS
Recognition
Effectiveness
Neutrality
Relevance
Standardization
CEN, the European Committee for Standardization, is one of 3 European
Standardization Organizations (together with CENELEC and ETSI) that have been officially
recognized by the European Union as being responsible for developing and
defining voluntary standards at European level.

6.
EUROPEAN ICT ROLES WITH FOCUS ON BIG DATA
6
The European ICT Professional Role Profiles (*) version 2 have
been officially published by CEN on 2018-08-29.
7 new Profiles have been added:
DATA SCIENTIST
DATA SPECIALIST
DEVOPS EXPERT
DIGITAL TRANSFORMATION ROLE
PRODUCT OWNER
SCRUM MASTER
SOLUTION DESIGNER
(*) CWA 16458-1:2018

7.
DATA SCIENTIST ROLE (1)
SUMMARY STATEMENT AND MISSION
7
Summary
statement
Leads the process of applying data analytics. Delivers
insights from data by optimising the analytics process
and presenting visual data representations.
Mission Finds, manages and merges multiple data sources and
ensures consistency of datasets. Identifies the
mathematical models, selects and optimises the
algorhythms to deliver business value through insights.
Communicates patterns and recommends ways of
applying data.

8.
DATA SCIENTIST ROLE (2)
MAIN TASK/S
8
Main task/s • Represents business challenges through mathematical
models
• Collect, understand, clean, analyse, integrate and
investigate internal and external data to achieve the
mission
• Create and test hypothesis
• Uncover data correlations/relationships in support of
measurement and predication
• Identify the right visualisation models depending on the
business challenges and the data sets
• Address data security through active preventative strategies
• Select and optimise algorhythms using data science tools
• Comply with ethical guidelines and legal requirements

9.
DATA SCIENTIST ROLE (3)
MAIN COMPETENCES
9
e-Competences
(from e-CF)
A.7. Technology Trend Monitoring Level 5
A.9. Innovating Level 4
D.10. Information and Knowledge
Management
Level 5
D.11. Needs Identification Level 4
E.1. Forecast Development Level 4

10.
THE FOUR PILLARS OF IT PROFESSIONALISM IN EUROPE
STATE OF THE ART OF EDUCATION, TRAINING AND CERTIFICATION, DATA PROFESSIONALS INCLUDED!
10
e-Competence performance indicators and
common metrics
Development of a Technical Report (CEN/TR)
expected to analysing and designing how to
recognise and assess that a candidate really
has the e-competences he/she declares to
possess, whenever/wherever such
competence have been acquired/developed.
32 months (started: 1st May 2019)
ICT Curriculum Guidelines for e-Competence
and Digital Leadership
Provide a TS on how to design, develop,
maintain, adjust and compare ICT curricula,
within the EU framework of the IT
professionalism
32 months (started: 1st August 2019)

11.
SO WHAT?
SOME PERSONAL CONSIDERATIONS FROM EXPERIENCE
11
Professionals in the field of Big Data need to be more on the
business side.
The relationship between IT and business within organization is
one of the key elements for a successful Digital Transformation.
This is particularly true in the field of Big Data.
Standardization is part of the game. Standardization of
competences is important and is possible. In my opinion it is the
future, too. Of course, in order to be feasible, it is necessary to
identify the right level of granularity.
A joint effort in the field of Big Data is needed and urgent, based
on the existing.

12.
I am happy to be contacted!
rocco.defina@oxysconsulting.it
https://www.linkedin.com/in/roccodefina/