MEIC: especialização em Processamento e Análise de Dados (aka Big Data ou Data Science ) Quase Tudo Sobre o MEIC, 2017

Transcrição

1 MEIC: especialização em Processamento e Análise de Dados (aka Big Data ou Data Science ) Quase Tudo Sobre o MEIC, 2017

2 Coordenador da Especialização Mário Gaspar da Silva Professor Catedrático Departamento de Engenharia Informática

3

4 Data Scientist

5 Tema: Data Science and Engineering conjunto transversal de temáticas que abrange várias áreas de ensino e investigação do DEI, desde os algoritmos e infraestruturas, aos sistemas inteligentes e de informação, e visualização interactiva de dados complexos.

6 part analyst, part artist. A data scientist represents an evolution from the business or data analyst role. The formal training is similar, with a solid foundation typically in computer science and applications, modeling, statistics, analytics and math. What sets the data scientist apart is strong business acumen, coupled with the ability to communicate findings to both business and IT leaders in a way that can influence how an organization approaches a business challenge. Good data scientists will not just address business problems, they will pick the right problems that have the most value to the organization

7 Volume

8 Cloud Computing

9 Map-Reduce Jeffrey Dean and Sanjay Ghemawat. MapReduce: Simplified Data Processing on 2017 Large IST Clusters. OSDI 2004

10 X-Info The evolution of X-Info and Comp-X for each discipline X How to codify and represent our knowledge Experiments & Instruments Other Archives facts Literature facts? questions answers Data ingest Managing a petabyte Common schema How to organize it How to reorganize it How to share with others Simulations The Generic Problems Query and Vis tools Building and executing models Integrating data and Literature Documenting experiments Curation and long-term preservation

11 From Big Science to Big Business Big Science Source: experiments and research conducted in controlled environments Goals: to answer questions, or prove theories Big Business Source: transactions in nature and little control Goals: to discover new opportunities, measure efficiencies, uncover relationships Common Need technologies to work with data Use algorithms to mine data

12 Disciplinas Processamento e Análise de Dados CNV CPD Computação em Nuvem e Virtualização Computação Paralela e Distribuída AID SAD VI Análise e Integração de Dados Sistemas de Apoio à Decisão Visualização de Informação

13 Responsáveis 2016/17 Processamento e Análise de Dados CNV CPD Prof. Luís Veiga Prof. José Monteiro AID SAD VI Prof. Helena Galhardas Prof. Andreas Wichert Prof. Daniel Gonçalves

14 How the Circle Line rogue train was caught with data

15 How the Circle Line rogue train was caught with data

16 How the Circle Line rogue train was caught with data

17 Investigação no IST

18 Sede: Tagus Tagus.

19 Tudo sobre o MEIC 2017 Epecialização em Processamento e Análise de Dados? mario.gaspar.silva@tecnico.ulisboa.pt