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Big Data




Wilson Lucas
           wilsonlucas@yahoo.com




                                   ©Wilson Lucas 2013
Apresentação




Wilson Lucas
           wilsonlucas@yahoo.com




                                   ©Wilson Lucas 2013
O que é o “Big Data”


                                                                     "Big data" is
                                                                     • high-volume,
                                                                     • high-velocity and
                                                                     • high-variety
                                                                     information assets that demand
                                                                     cost-effective, innovative forms of
                                                                     information processing for
                                                                     enhanced insight and decision
                                                                     making.


 An enhanced insight that leads to improved decision making and value
                               creation.
Source: The Importance of 'Big Data': A Definition, Mark Beyer, Douglas Laney, G00235055
                                                                                                       ©Wilson Lucas 2013
Big Data

“80% of data is now unstructured content such as email, videos,
  and other user-generated content which must be combined
  with structured data to produce the information businesses
            need to serve consumers individually.”

 Weblogs, social media, server logs, sensores, emails, fotografias.

 O crescimento da electrónica de consumo, a baixa de preços continuada
 de processadores, armazenamento e comunicações.


 Transformação : o potencial destes dados pode agora ser explorado
 pelas organizações.

  Aumento do valor estratégico da informação.

       “Infonomics is recent term to describe the study and emergent discipline of
       quantifying, managing and leveraging information as a formal business asset.”
       wikipedia
                                                                        ©Wilson Lucas 2013
Big Data
• Volume
Crescimento rápido de dados estruturados, não estruturados, internos e
 externos. Ex: Um motor a jacto produz cerca de 10TB de dados em 30 minutos...

• Velocidade
Necessidades de negócio não antecipadas.
Ex: Fluxo de opiniões e relações geradas,
alta velocidade e frequência dos tweets

• Variedade
Vários formatos, diferindo dos tradicionais com taxas de mudança bastante altas.
  Novos tipos de dados serão necessários para capturar a informação resultante.
Ex: novos sensores implementados, novas campanhas de marketing executadas

• Valor
Existe pouco valor per se nestes dados.
Ex: Se perdermos 5 minutos das transacções de um cliente numa webstore, não irá
  influenciar a analise sobre o seu comportamento.
                                                                            ©Wilson Lucas 2013
Alguns cenários de utilização




                                ©Wilson Lucas 2013
Alguns cenários de utilização

    Desafio actual              Novos dados              Possibilidades
  Cuidados de Saúde:       Monitorização remota do    Cuidados preventivos,
                                   paciente          hospitalização reduzida
deslocação e consultas
     dispendiosas
      Fabricação:           Sensores de produto      Diagnostico automático
  Suporte presencial
 Serviços com base em      Dados de localização em   Geo-advertising, tráfego,
 localização geográfica          tempo real               busca local
    Sector Publico:        Inquéritos dos cidadãos     Serviços à medida,
    Serviços padrão                                     redução de custos
  Comercio e retalho:           Social media         Analise de sentimento e
Marketing “generalizado”                                  segmentação


                                                                         ©Wilson Lucas 2013
Realidade vs. Ficção




                       ©Wilson Lucas 2013
Tendências




             ©Wilson Lucas 2013
Tendências
Hype Cycle for emerging technologies


   




                                       ©Wilson Lucas 2013
Aplicado ao Marketing




                        ©Wilson Lucas 2013
Questões que o Negócio quer ver resolvidas




Gartner




                                                   ©Wilson Lucas 2013
Exemplo: Consumer Analytics




                              ©Wilson Lucas 2013
Information Storage 2020
    Mito da BD como única fonte de informação


                       …No DISK, No SQL, Very Cloudy




    2011
                        • Content File Store
•   DBMS                • DBMS Cloud Services
                        • Column Store DBMS
                        • noSQL
                        • In-Memory DBMS
                        • Big Data Solutions

                                                ©Wilson Lucas 2013
Tecnologia




             ©Wilson Lucas 2013
O papel da tecnologia
• Hadoop project
It is a framework which allows processing of large data sets across cluster of
computers (commodity hardware).

Hadoop MapReduce Its a programming mode which supports parallel processing of
large datasets




                                                http://gigaom.com/cloud/what-it-really-means-when-someone-says-hadoop/


                                                                                                       ©Wilson Lucas 2013
O papel da tecnologia
• Ecossistema Hadoop




                                  http://tushar686.wordpress.com/2012/04/04/hadoop-and-mapreduce//



                                                                                      ©Wilson Lucas 2013
Tecnologia


"How to Choose the Right Apache Hadoop Distribution" — Vendors offer
Apache Hadoop distributions with preintegrated projects, but different
vendors offer different combinations, at differing release levels.”

“Interest in using Hadoop to solve big data challenges has increased
significantly in the past 12 months. “

“IT architects, business leaders and data scientists involved in "big data"
projects can easily go wrong when they construct an Apache Hadoop
stack, because the 20 or more potential components ("projects") are not
integrated as commercial software packages are.”




                                                                      ©Wilson Lucas 2013
©Wilson Lucas 2013
IBM Will Boost Analytics Ability by Buying Search Provider Vivisimo

Aster Data Purchase Shows Teradata's Vision Is Deeper Than 'Big Data'
The planned acquisition of Aster Data will give Teradata a distributed data warehouse that
supports unstructured content and more aspects of extreme data than competitors do now.

Netezza Acquisition Will Boost IBM Against Oracle, Teradata

Hadoop Distribution Seeks to Leverage Intel's Microprocessor Strengths



Acquire, organize, and analyze big data

Uncover hidden relationships that lead to new perspectives

Turn analytics into better decision-making



  É fundamental perceber o que os dados significam para a organização.
                                                                                   ©Wilson Lucas 2013
Investimento




               ©Wilson Lucas 2013
Investimento




“Big Data Drives Rapid Changes in Infrastructure and $232 Billion in IT Spending
through 2016
Big data has become a major driver of IT spending. The benefits to organizations
for adding big data to their information management and analytics infrastructure
will force a more rapid cycle of replacing existing solutions.”
                                                                       ©Wilson Lucas 2013
Comparison of Data Characteristics by Industry




                           Media and Services




                                                                                                  Manufacturing and
                                                                                                  Natural Resources
                           Communications,




                                                                                                                                                            Wholesale Trade
                                                                                                                               Transportation
           Banking and




                                                            Government


                                                                         Healthcare
                                                Education
           Securities




                                                                                      Insurance
                                                                         Providers




                                                                                                                                                Utilities
                                                                                                                      Retail
Volume
of Data
Velocity
of Data
Variety
of Data

                         Potential big data opportunity on each dimension is:
                         Very hot (compared with other industries)
                         Hot
                         Moderate
                         Low
                         Very low (compared with other industries)




                                                                                                                                                                              ©Wilson Lucas 2013
Comparison o Spending Intensity by Industry




                           Media and Services




                                                                                                  Manufacturing and
                                                                                                  Natural Resources
                           Communications,




                                                                                                                                                            Wholesale Trade
                                                                                                                               Transportation
           Banking and




                                                            Government


                                                                         Healthcare
                                                Education
           Securities




                                                                                      Insurance
                                                                         Providers




                                                                                                                                                Utilities
                                                                                                                      Retail
Hardware


Software


Services


                         Potential big data opportunity on each dimension is:
                         Very hot (compared with other industries)
                         Hot
                         Moderate
                         Low
                         Very low (compared with other industries)




                                                                                                                                                                              ©Wilson Lucas 2013
Big Data




 Obrigado!



Wilson Lucas
         wilsonlucas@yahoo.com

                                 ©Wilson Lucas 2013

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Everis big data_wilson_v1.4

  • 1. Big Data Wilson Lucas wilsonlucas@yahoo.com ©Wilson Lucas 2013
  • 2. Apresentação Wilson Lucas wilsonlucas@yahoo.com ©Wilson Lucas 2013
  • 3. O que é o “Big Data” "Big data" is • high-volume, • high-velocity and • high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.  An enhanced insight that leads to improved decision making and value creation. Source: The Importance of 'Big Data': A Definition, Mark Beyer, Douglas Laney, G00235055 ©Wilson Lucas 2013
  • 4. Big Data “80% of data is now unstructured content such as email, videos, and other user-generated content which must be combined with structured data to produce the information businesses need to serve consumers individually.” Weblogs, social media, server logs, sensores, emails, fotografias. O crescimento da electrónica de consumo, a baixa de preços continuada de processadores, armazenamento e comunicações. Transformação : o potencial destes dados pode agora ser explorado pelas organizações.  Aumento do valor estratégico da informação. “Infonomics is recent term to describe the study and emergent discipline of quantifying, managing and leveraging information as a formal business asset.” wikipedia ©Wilson Lucas 2013
  • 5. Big Data • Volume Crescimento rápido de dados estruturados, não estruturados, internos e externos. Ex: Um motor a jacto produz cerca de 10TB de dados em 30 minutos... • Velocidade Necessidades de negócio não antecipadas. Ex: Fluxo de opiniões e relações geradas, alta velocidade e frequência dos tweets • Variedade Vários formatos, diferindo dos tradicionais com taxas de mudança bastante altas. Novos tipos de dados serão necessários para capturar a informação resultante. Ex: novos sensores implementados, novas campanhas de marketing executadas • Valor Existe pouco valor per se nestes dados. Ex: Se perdermos 5 minutos das transacções de um cliente numa webstore, não irá influenciar a analise sobre o seu comportamento. ©Wilson Lucas 2013
  • 6. Alguns cenários de utilização ©Wilson Lucas 2013
  • 7. Alguns cenários de utilização Desafio actual Novos dados Possibilidades Cuidados de Saúde: Monitorização remota do Cuidados preventivos, paciente hospitalização reduzida deslocação e consultas dispendiosas Fabricação: Sensores de produto Diagnostico automático Suporte presencial Serviços com base em Dados de localização em Geo-advertising, tráfego, localização geográfica tempo real busca local Sector Publico: Inquéritos dos cidadãos Serviços à medida, Serviços padrão redução de custos Comercio e retalho: Social media Analise de sentimento e Marketing “generalizado” segmentação ©Wilson Lucas 2013
  • 8. Realidade vs. Ficção ©Wilson Lucas 2013
  • 9. Tendências ©Wilson Lucas 2013
  • 10. Tendências Hype Cycle for emerging technologies  ©Wilson Lucas 2013
  • 11. Aplicado ao Marketing ©Wilson Lucas 2013
  • 12. Questões que o Negócio quer ver resolvidas Gartner ©Wilson Lucas 2013
  • 13. Exemplo: Consumer Analytics ©Wilson Lucas 2013
  • 14. Information Storage 2020 Mito da BD como única fonte de informação …No DISK, No SQL, Very Cloudy 2011 • Content File Store • DBMS • DBMS Cloud Services • Column Store DBMS • noSQL • In-Memory DBMS • Big Data Solutions ©Wilson Lucas 2013
  • 15. Tecnologia ©Wilson Lucas 2013
  • 16. O papel da tecnologia • Hadoop project It is a framework which allows processing of large data sets across cluster of computers (commodity hardware). Hadoop MapReduce Its a programming mode which supports parallel processing of large datasets http://gigaom.com/cloud/what-it-really-means-when-someone-says-hadoop/ ©Wilson Lucas 2013
  • 17. O papel da tecnologia • Ecossistema Hadoop http://tushar686.wordpress.com/2012/04/04/hadoop-and-mapreduce// ©Wilson Lucas 2013
  • 18. Tecnologia "How to Choose the Right Apache Hadoop Distribution" — Vendors offer Apache Hadoop distributions with preintegrated projects, but different vendors offer different combinations, at differing release levels.” “Interest in using Hadoop to solve big data challenges has increased significantly in the past 12 months. “ “IT architects, business leaders and data scientists involved in "big data" projects can easily go wrong when they construct an Apache Hadoop stack, because the 20 or more potential components ("projects") are not integrated as commercial software packages are.” ©Wilson Lucas 2013
  • 20. IBM Will Boost Analytics Ability by Buying Search Provider Vivisimo Aster Data Purchase Shows Teradata's Vision Is Deeper Than 'Big Data' The planned acquisition of Aster Data will give Teradata a distributed data warehouse that supports unstructured content and more aspects of extreme data than competitors do now. Netezza Acquisition Will Boost IBM Against Oracle, Teradata Hadoop Distribution Seeks to Leverage Intel's Microprocessor Strengths Acquire, organize, and analyze big data Uncover hidden relationships that lead to new perspectives Turn analytics into better decision-making  É fundamental perceber o que os dados significam para a organização. ©Wilson Lucas 2013
  • 21. Investimento ©Wilson Lucas 2013
  • 22. Investimento “Big Data Drives Rapid Changes in Infrastructure and $232 Billion in IT Spending through 2016 Big data has become a major driver of IT spending. The benefits to organizations for adding big data to their information management and analytics infrastructure will force a more rapid cycle of replacing existing solutions.” ©Wilson Lucas 2013
  • 23. Comparison of Data Characteristics by Industry Media and Services Manufacturing and Natural Resources Communications, Wholesale Trade Transportation Banking and Government Healthcare Education Securities Insurance Providers Utilities Retail Volume of Data Velocity of Data Variety of Data Potential big data opportunity on each dimension is: Very hot (compared with other industries) Hot Moderate Low Very low (compared with other industries) ©Wilson Lucas 2013
  • 24. Comparison o Spending Intensity by Industry Media and Services Manufacturing and Natural Resources Communications, Wholesale Trade Transportation Banking and Government Healthcare Education Securities Insurance Providers Utilities Retail Hardware Software Services Potential big data opportunity on each dimension is: Very hot (compared with other industries) Hot Moderate Low Very low (compared with other industries) ©Wilson Lucas 2013
  • 25. Big Data Obrigado! Wilson Lucas wilsonlucas@yahoo.com ©Wilson Lucas 2013