Apresentação : "Desafios e Oportunidades derivados da Explosão de Dados (Big Data) ": nas Jornadas ANPRI - Associação Nacional dos Profissionais de Informática - em Coimbra no dia 16 de Junho de 2012 - Por Francisco Lavrador Pires : FB - https://www.facebook.com/francisco.l.pires ; Twitter @flpires

1. O Profissional de Informática :
Desafios e Oportunidades derivadas da Explosão de
Dados (Big Data)
TENDÊNCIAS (New Skills)
COMPETÊNCIAS
INTRODUÇÃO
OPORTUNIDADES DESAFIOS
BIG &
SUGESTÕES
DATA
Coimbra, 16 de Junho de 2012
eLearning Club – Francisco Lavrador Pires

2. O1 O2 O3
Introdução Tendências Competências
O4 O5 O6
BIG DATA Oportunidades Desafios
O7
Sugestões

3. O1
Introdução

4. O1
Introdução
12 Top Big Data Analytics Players
http://www.informationweek.com/news/galleries/software/bi/231900870

5. The Glory of Big Data
Suddenly, we can know the world completely. Next, we reprogram it O1
Introdução
In 2011 the volume of available data is
predicted to continue along its exponential
growth curve to 1.8 zettabytes.
(A zettabyte is a trillion gigabytes;
that’s a 1 with 21 zeros trailing behind it.)
http://www.popsci.com/technology/article/2011-10/glory-big-data

6. O1
Introdução

7. O que queremos dizer
quando falamos de Dados ?
O1
Introdução

8. O1
Introdução
http://www.foodshare.net/school-crunch.htm
http://www.popsci.com/announcements/article/2011-10/november-2011-data-power

9. O1
Introdução
As the industry matures, it will raise a set of quandaries that we should start t
hinking about now. Here are the six with suggested solutions:
Privacy: The dilemma is managing the tension between privacy and openness.
The solution is allowing individuals to correct their own data. Upcoming
technology should enable this.
Information Security: The 2003 Californian law requiring companies to
notify customers of security breaches pushes companies to invest in prevention
Digital Records: A call for automatic deletion of expired digital records.
Yet legislation is moving in the opposite direction.
Processing Data: Data might promote racial or other discrimination.
Solution: regulate against using an individual’s data against him or her on the
basis of something that may or may not happen.
Personal Information as a Property Right: You own your photos, not
facebook. Data portability will promote competition, just as cell phone
number portability did.
Integrity of the Information: The World Trade Organization should legislate
to protect the data commons.
Big picture stuff, of course. But refreshingly constructive and practical.
It seems like the marketing industry should identify its own subset of issues
and address them in a similar spirit.
http://thedoublethink.com/2010/03/big-data/

10. O2
Tendências

11. SIX DRIVERS OF CHANGE …
O2
Tendências
2-RISE OF SMART 3-COMPUTATIONAL
1-EXTREME MACHINES AND WORLD
(Massive increases in
LONGEVITY SYSTEMS sensors and processing
(Increasing global (Workplace automation power make the world
lifespans change the nudges human a programmable
nature of careers workers out of rote, systemOperativo)
and learning ) repetitive tasks )
4-NEW MEDIA 5-SUPERSTRUCTUD
ORGANIZATIONS 6 - GLOBALY
ECOLOGY CONNECTD
(New communication ( Social technologies
tools require new drive new forms of WORLD
media literacies production and value (Increased global
beyond text) Creation ) interconnectivity
puts diversity and
adaptability at the center
of organizational
operations
Fonte : Institute for the Future for the University of Phoenix Research Institute
Nota : Há quem arrisque um Cronograma com «datas»e tudo. Pensamos no entanto que as memes (ainda em Inglês), como
“social media”,“social business”,” social thinking “, “social relationship management “etc… vão fazer o seu caminho
e aqui no eLearning Club vamos estar atentos pois acreditamos que o futuro do eLearning pode ser “Aprendizagem Social” 

12. Prepare the Aftermath …
O2
Tendências

13. O3
Competências

14. FUTURE WORK SKILLS
The skills for the Future Workforce
1 – Sense-making;
O3
Competências
2 – Social Intelligence;
3 – Novel & Adaptive Thinking;
4 – Cross-Cultural Competency;
5 – Computational Thinking;
6 – New-Media Literacy;
7 – Transdisciplinarity;
8 – Design Mindset;
9 – Cognitive Load Management;
10 – Virtual Collaboration

15. Big Data Analytics Framework
O3
Competências

16. O3
Competências

17. TUTORIAL
Tipos de Plataformas Analíticas :
O3
Competências
1 - MPP : Massively parallel processing analytic
databases
2 - Columnar databases
3 - Analytical appliances
4 - Analytical bundles
5 - In-memory databases
6 - Distributed filebased Systems
7 - Analytical services
8 - Nonrelational
9 - CEP/streaming engines

18. FERRAMENTAS: O3
Competências

19. O4
Big Data

20. O4
BIG DATA

21. The Internet of Things O4
BIG DATA

22. Where Data lives ?
The Ten Most Amazing Databases in the World
A database isn't a vault--it's a garden
O4
By Rena Marie Pacella BIG DATA
The Combined DNA Index System
The Encyclopedia of Life
The Food and Agriculture Organization Database
The Genographic Project
The International Panel on Climate Change's Data
Distribution Centre
The MD:Pro
OKCupid's OKTrends
Sloan Digital Sky Survey Database
The Wayback Machine
WorldCat
http://www.popsci.com/technology/article/2011-10/ten-most-amazing-databases-world
Fonte : http://www.popsci.com/announcements/article/2011-10/november-2011-data-power

23. “The impact of Big Data on
business differentiation” O4
BIG DATA
Taking the teams through examples, theories and definitions, he also t
alked about the emergence of “Data Scientist.” Take a look at this graph,
illustrating how Data Scientists are a result of using Big Data through
verticals.
http://founderfuel.com/2011/09/12/day-21-week-5-starts-big-with-talks-about-big-data/

24. O Cidadão na Rede (KSA + VBP ) O4
BIG DATA
Digital Citizenship
Crowd Participation
Sharing and Collaboration
Soft Skills
http://digitalmarketing2.com/

25. O4
BIG DATA
http://www.joeydevilla.com/2009/07/13/where-does-the-money-go/

26. O5
Oportunidades

27. O Profissional de O5
Oportunidades
Informática
O Ambiente de Trabalho

28. Informática
Bioinformática
Informática
Médica
Aplicada ao
Jornalismo de
Dados
O5
Oportunidades
Informática
Informática
de Saude
Informática De Ensino/Aprendizagem
Forense
Informática
Informática de Industrial
Informática Enfermagem
Aplicada à Informática Informática
Informática
Robótica de Computação de Supervisão
Estética
Intensiva Ecoinformática e Defesa
Informática
Informática de Informática Aumentada (Virtual)
Tempo Real Gestual
Informática
Informática
Informática Clínica
Informática Móvel
da Nuvem
de Interação e Informática
Relacionamento Algorítmica

29. O5
Oportunidades

30. O6
Desafios

31. O6
Desafios
http://www.enterprisecioforum.com/en/blogs/tberger/big-data-king-terabytes

32. O6
Data Scientist » Data Geek » Data Designer
Desafios
http://datavisualization.ch/opinions/data_scientist-data_geek-data_designer/

33. Onde está o Negócio ? O6
Desafios
http://radar.oreilly.com/2012/01/the-feedback-economy.html

34. Onde está o Negócio ? O6
Desafios
http://radar.oreilly.com/2012/01/the-feedback-economy.html

35. O7
Sugestões

36. eLearning Club : Facebook Group
https://www.facebook.com/groups/eLearningNetwork/
O7
Sugestões

37. O7
Sugestões

38. Big Data na Educação/ Formação e Coaching
Definitions:
Learning analytics:
The measurement, collection, analysis and reporting of data
O7
about learners and their contexts, for purposes of Sugestões
understanding and optimizing learning and the environments
in which it occurs. (SoLAR: http://www.solaresearch.org/about/)
Academic analytics:
Academic analytics marries large data sets with statistical techniques and predictive
modeling to improve decision making. (Campbell and Oblinger, 2007:
http://net.educause.edu/ir/library/pdf/PUB6101.pdf)
Educational Data Mining:
Educational Data Mining is an emerging discipline, concerned with developing
methods for exploring the unique types of data that come from educational settings,
and using those methods to better understand students, and the settings which they
learn in.
Whether educational data is taken from students' use of interactive learning
environments, computer-supported collaborative learning, or administrative data
from schools and universities, it often has multiple levels of meaningful hierarchy,
which often need to be determined by properties in the data itself, rather than in
advance. Issues of time, sequence, and context also play important roles in the study
of educational data. (IEDMS: http://www.educationaldatamining.org/)
http://lak12.wikispaces.com/Week2_Defining_Analytics

39. O7
Sugestões

40. O7
Sugestões
Pensamento Computacional
Liderança de Comunidades
Iniciativas Orientadas à Sociedade

41. O7
Sugestões
If Knowledge can create problems,
It is not through ignorance
that we can solve them.
Isaac Asimov

42. O Profissional de Informática :
Desafios e Oportunidades derivadas da Explosão de
Dados (Big Data)
TENDÊNCIAS (New Skills)
COMPETÊNCIAS
INTRODUÇÃO
OPORTUNIDADES DESAFIOS
BIG &
SUGESTÕES
DATA
OBRIGADO ;)
eLearning Club – Francisco Lavrador Pires