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Big Data: Perspectivas
atuais e futuras.
Cezar Taurion
Executivo de Novas Tecnologias
Chief Evangelist
ctaurion@br.ibm.com
TUDO EM
TEMPO REAL
TECNOLOGIA
PERVASIVA E
COMPUTAÇÃO
SOCIAL

UMA NOVO
AMBIENTE DE
TRABALHO

A SOCIEDADE
HIPERCONECTADA

UM...
Celulares/ smartphones/tablets já se igualam em numero à
população do planeta…
… and this isn’t just about
connecting people
We are building systems of systems
Latest generation car:
100 electronic con...
The Connected Vehicle – ‘A System of
systems’
ANALYTICS SYSTEMS
• Vehicle Condition Monitoring
• Prognostics
• Advanced Di...
Forecasts call for billions and
billions of connected devices

Ericsson CEO
Hans Vestberg
estimates 50 billion
devices wil...
2012: 2800 Bilhões de GB!
Big Data refers to how to collect, store, and
manage information that comes into an
enterprise so that it can be harvested...
Traditional Approach

New Approach

Structured, analytical, logical

Creative, holistic thought, intuition

Hadoop
Streami...
“Clearly, the big data revolution is fostering a
powerful new type of data science. Having
more comprehensive data sets at...
15
Adoção de Big data
'Big Data' está ainda no canto da tela do radar dos CIOs/CEOs/Gestores…

Most are already debating/
eva...
Clients are in an exploratory phase analyzing traditional
data types to address challenges around Operations &
Customer Ex...
Sentiment Analysis
Novas técnicas de visualização
The rise of the Data Scientist in 2013

“A data scientist is someone who can
understand the desired business
outcome, exam...
Big Data impacta todos setores de negócio…
SW Business Use Cases

Banking
Single View of Customer
Customer Centric
Asset O...
Como agir?

Strategy

Technology

Organization

Sponsorship

Expertise

Culture

Establish a common vision
to guide action...
Como agir?

1
Multiple Data
Sources
Creatively source internal
& external data
Upgrade IT architecture
and infrastructure ...
Cezar Taurion
ctaurion@br.ibm.com
https://www.ibm.com/developerworks/community/
blogs/ctaurion/?lang=en
@ctaurion
Facebook...
Big data: status atual e tendências
Big data: status atual e tendências
Big data: status atual e tendências
Big data: status atual e tendências
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Big data: status atual e tendências

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Palestra sobre status atual de Big data e tendências para os próximos anos

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Big data: status atual e tendências

  1. 1. Big Data: Perspectivas atuais e futuras. Cezar Taurion Executivo de Novas Tecnologias Chief Evangelist ctaurion@br.ibm.com
  2. 2. TUDO EM TEMPO REAL TECNOLOGIA PERVASIVA E COMPUTAÇÃO SOCIAL UMA NOVO AMBIENTE DE TRABALHO A SOCIEDADE HIPERCONECTADA UMA NOVA GERAÇÃO
  3. 3. Celulares/ smartphones/tablets já se igualam em numero à população do planeta…
  4. 4. … and this isn’t just about connecting people We are building systems of systems Latest generation car: 100 electronic controllers 10 million lines of code Its own IP address Developed in 29 months (usually a 60-120 month process) General Motors - 2011 Chevy Volt http://ibm.co/btsi5C
  5. 5. The Connected Vehicle – ‘A System of systems’ ANALYTICS SYSTEMS • Vehicle Condition Monitoring • Prognostics • Advanced Diagnostics • SW fault analytics • Vehicle Repair GPS NETWORK Satellite Cellular (WAN) Vehicle Control Unit GSM IP GPRS NETWORK PLMN BUSINESS SYSTEMS • Customer Support • Service Data • Warranty Data WiFi Zone ICOM DCAN Ethernet Most Bytefligh FlexRay CAN ECU 1 Vehicle and Road Data ECU n Dealer PDA Vehicle-toVehicle Vehicle to Roadside Tolling EV/Hybrid Charging PARTNER SYSTEMS • Police/Emergency • Weather • Traffic • Concierge • Vehicle registration • Bank • Helpdesk • Government • Utilities • Insurance (pay as you go)
  6. 6. Forecasts call for billions and billions of connected devices Ericsson CEO Hans Vestberg estimates 50 billion devices will be connected to the Web by 2020 50 Billion Connections in 2020 – Ericsson (from page 18 of 2010 annual report) 9
  7. 7. 2012: 2800 Bilhões de GB!
  8. 8. Big Data refers to how to collect, store, and manage information that comes into an enterprise so that it can be harvested for decision making 12
  9. 9. Traditional Approach New Approach Structured, analytical, logical Creative, holistic thought, intuition Hadoop Streaming Data Data Warehouse Transaction Data Web Logs, URLs Text data: emails, chats Internal App Data Mainframe Data Structured Repeatable Linear Enterprise Integration Unstructured Exploratory Iterative OLTP System Data ERP data Social Data RFID, sensor data Traditional Sources New Sources Network Data
  10. 10. “Clearly, the big data revolution is fostering a powerful new type of data science. Having more comprehensive data sets at our disposal will enable more fine-grained longtail analysis, microsegmentation, next best action, customer experience optimization, and digital marketing applications” – Forrester
  11. 11. 15
  12. 12. Adoção de Big data 'Big Data' está ainda no canto da tela do radar dos CIOs/CEOs/Gestores… Most are already debating/ evaluating/ considering 'Big Data' Some are just starting to explore 'Big Data' Several plan to implement w/in the near future Only a minority has not looked/ won't look into it Ignorants 16 Early Explorers Adoção Heavy Explorers A few are already/ still implementing 'Big Data' Planners Implementors
  13. 13. Clients are in an exploratory phase analyzing traditional data types to address challenges around Operations & Customer Experience Key imperatives for clients implementing Big Data technologies Top business imperatives for using Big Data technologies: Improve Improve operational operational efficiency from efficiency from machine data machine data Intelligent Infrastructure Management Grow, retain & Grow, retain & satisfy satisfy customers customers Real-time Call Data Record Analytics Optimize building energy consumption with centralized monitoring Automate preventive and corrective maintenance Organizations are analyzing traditional types of data – most often Customer & Transaction data Real-time mediation and analysis of 6B CDRs per day Data processing time reduced from 12 hrs to 1 sec Hardware cost reduced to 1/8th Q: What type of data are organizations analysing most? n = 163 Source: Ventana Research – The Challenge of Big Data Benchmark Research 17
  14. 14. Sentiment Analysis
  15. 15. Novas técnicas de visualização
  16. 16. The rise of the Data Scientist in 2013 “A data scientist is someone who can understand the desired business outcome, examine the data, and create hypotheses about how to establish predictive rules that can enable business outcomes such as increasing eCommerce upsell, keeping a production line running, or eliminating stock-outs” – Forrester 20 Data Scientist: The Sexiest Job of the 21st Century – Harvard Business Review
  17. 17. Big Data impacta todos setores de negócio… SW Business Use Cases Banking Single View of Customer Customer Centric Asset Optimization Security Enterprise Ops Risk Mgmt Credit Lifecycle Mgmt Next Best Action Fraud – AML Digital Adoption Media and Entertainment • • Audience Insight Business process transformation Automotive Actionable Consumer Intelligence Predictive Asset Optimization (Equip Health & Mfg Quality and SCO) Insurance Telco Solvency II Antifraud, Waste, Abuse Next Best Action Operational Risk Policy Analytics Claims Analytics Single View of Customer Centralized BI Delivery Center EDW and BI Transformation Call Detail Record Analytics Advanced Analytics Lab Next Best Action Predictive Asset Optimization Network Analytics Travel and Transport Customer Loyalty & Insights Dynamic Social Media Recommendations Chemical and Petroleum Turnaround Management Performance Mgmt System Drilling Analytics Master Data Management Consumer Products • • • Post Event Analysis and Tracking (DSR) Shelf Availability (SW) Promotional Spend Optimization (SW) Merchandising Compliance (SW) Industrial Products Production Design and Optimization Scheduling Energy & Utilities Retail Customer Driven Loyalty Marketing Collaborative Analytics Platform Intelligent Ops Center Customer MDM Social Media Segmentation Power Delivery Dashboard CFO Performance Insight Smart Meter Customer Insight Grid Analytics Risk Analytics Condition Based Maintenance Government Social Program Integrity Citizen Access and Insight Border Control Management Customs Risk Management Road User Charging Electronics Predictive Asset Optimization Customer Analytics Quality Early Warning System Supply Chain Analytics Healthcare • • Customer Segmentation and Member Analytics Measure & Act on Population Health Outcomes (SW) Engage Consumers in their Healthcare (SW) Life Sciences Strategic Insight Portfolio (SIIP) Clinical Research Library Patient Adherence
  18. 18. Como agir? Strategy Technology Organization Sponsorship Expertise Culture Establish a common vision to guide actions and deliver value Increase knowledge-sharing opportunities Make decision based on facts Source of Value Data Measurement Ensure alignment between analytic focus and value creation Create confidence with governance and security Measure impact and model the future Funding Platform Trust Create value with rigor and collaboration Integrate hardware and software to manage big data Create trustworthy relationships Source: Analytics: A blueprint for value – Converting big data and analytics into results, IBM Institute for Business Value © 2013 IBM 22
  19. 19. Como agir? 1 Multiple Data Sources Creatively source internal & external data Upgrade IT architecture and infrastructure for easy merging of data 2 Prediction & Optimisation Models 3 Organizational Transformation Focus on the biggest drivers of performance Create simple, understandable tools for people on the frontline. Build models that balance complexity with ease of use Update processes and develop capabilities to enable tool use Source : Making Advanced Analytics Work for You : A practical guide to capitalize on Big Data; Harvard Business Review, Oct. 2012
  20. 20. Cezar Taurion ctaurion@br.ibm.com https://www.ibm.com/developerworks/community/ blogs/ctaurion/?lang=en @ctaurion Facebook e Linkedin Obrigado pela Atenção

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