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Afinal o que é Big data?


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Palestra sobre conceitos Big data no evento IDETI em SP. Aborda o que é Big data, debate alguns beneficios e desafios. Debate também o papel do CDO- Chief Data Officer.

Published in: Technology

Afinal o que é Big data?

  1. 1. Afinal, o que é Big Data? Como vai afetar as empresas e nossas vidas? Cezar Taurion Consultor senior
  3. 3. Midias sociais fazem parte do dia a dia do brasileiro
  4. 4. Celulares/ smartphones/tablets já se igualam em numero à população do planeta…
  5. 5. As coisas acontecem muito rapido no mundo cada vez mais hiperconectado
  6. 6. Quem é esta geração digital?  Usam tecnologias digitais no seu dia a dia e esperam usá-las no trabalho. São early adopters por natureza.  Entram no mundo online cada vez mais cedo... usam a Internet como laboratório social, para testar limites do relacionamento. Vivem em ritmo cada vez mais acelerado e são multitarefas (usam celular, MP3, tablet, smart TV...tudo ao mesmo tempo!)
  7. 7. Computing is not about computers anymore. It is about living!
  8. 8. 2007 7% 93% 2000 75% 25% 2013 2% 98% Digitalização dos dados e informações cresce em ritmo acelerado!
  9. 9. 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 22
  10. 10. Big Data and analytics unlock new insights and opportunities that just weren’t possible before Analytics Applied to Big Data 1. Better, smarter insights highlighting business opportunities—internal and external 2. Internal process and performance improvement 3. Creating novel, incremental revenue possibilities Traditional Approach Structured, analytical, logical Multimedia Data Warehouse Web Logs Social Data Sensor data: images RFID Internal App Data Transaction Data Mainframe Data OLTP System Data Traditional Sources ERP Data Structured Repeatable Linear Unstructured Exploratory Dynamic Text Data: emails Hadoop and Streams New Sources New Approach Creative, holistic, intuitive 23 Volume, Variety, Velocity, Veracity = Value Decem Big Data & Analytics North America | IBM Confidential
  11. 11. E você ainda pensava que lia sozinho(a)?
  12. 12. Você não é mais um anônimo... On Internet, they know you’re a four-year-old male dog that has fleas, prefers canned dog food and was neutered six months after birth, and this data is for sale for a fraction of a cent in mass quantities...
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  15. 15. Novas técnicas de visualização
  16. 16. Biases in social media data Digital access Age Class Gender Literacy Geography Optimism Position on issues Fans/opponents ...
  17. 17. Biases in social media data Digital access Age Class Gender Literacy Geography Optimism Position on issues Fans/opponents ...
  18. 18. Sentiment Analysis
  19. 19. Big Data impacta todos setores de negócio… Insurance  Solvency II  Antifraud, Waste, Abuse  Next Best Action  Operational Risk  Policy Analytics  Claims Analytics  Single View of Customer Banking  Single View of Customer  Customer Centric  Asset Optimization  Security  Enterprise Ops Risk Mgmt  Credit Lifecycle Mgmt  Next Best Action  Fraud – AML  Digital Adoption Telco  Centralized BI Delivery Center  EDW and BI Transformation  Call Detail Record Analytics  Advanced Analytics Lab  Next Best Action  Predictive Asset Optimization  Network Analytics Energy & Utilities  Power Delivery Dashboard  CFO Performance Insight  Smart Meter  Customer Insight  Grid Analytics  Risk Analytics  Condition Based Maintenance Media and Entertainment • Audience Insight • Business process transformation Retail  Customer Driven Loyalty Marketing  Collaborative Analytics Platform  Intelligent Ops Center  Customer MDM  Social Media Segmentation Travel and Transport Consumer Products  Post Event Analysis and Tracking (DSR) • Shelf Availability (SW) • Promotional Spend Optimization (SW) • Merchandising Compliance (SW) Government  Social Program Integrity  Citizen Access and Insight  Border Control Management  Customs Risk Management  Road User Charging Healthcare Automotive  Actionable Consumer Intelligence  Predictive Asset Optimization (Equip Health & Mfg Quality and SCO) Life Sciences  Strategic Insight Portfolio (SIIP)  Clinical Research Library  Patient Adherence Chemical and Petroleum  Turnaround Management  Performance Mgmt System  Drilling Analytics  Master Data Management Industrial Products Electronics  Predictive Asset Optimization  Customer Analytics  Quality Early Warning System  Supply Chain Analytics  Customer Loyalty & Insights  Dynamic Social Media Recommendations  Production Design and Optimization Scheduling  Customer Segmentation and Member Analytics • Measure & Act on Population Health Outcomes (SW) • Engage Consumers in their Healthcare (SW)
  20. 20. 34 'Big Data' está ainda no canto da tela do radar dos CIOs/CEOs/Gestores… Adoção de Big data Some are just starting to explore 'Big Data' Most are already debating/ evaluating/ considering 'Big Data' Adoção A few are already/ still implementing 'Big Data' Several plan to implement w/in the near futureOnly a minority has not looked/ won't look into it Ignorants Early Explorers Heavy Explorers Planners Implementors
  21. 21. The hype of big data continues, but in 2014/2015 the focus will be on implementing solutions and finding value Big Data: A 2014 HorizonWatch Trend Report “The hype around big data continues to drive increased investment and attention, but there is real substance behind the hype. Our survey underlines the fact that organizations across industries and geographies see 'opportunity' and real business value rather than the 'smoke and mirrors' with which hypes usually come.” – Gartner “The hype around big data is coming to an end, signifying the beginning of a long-term adoption trend that will expose myriad opportunities and challenges.” – IDC “The reality will set in as more organizations attempt Big Data and analytics initiatives. The opportunities are real, but still involves quite a bit of trial and error, and experimentation.” – IDC
  22. 22. Big Data: A 2014 HorizonWatch Trend Report Industry Analysts are forecasting significant growth in IT spending associated with the Big Data
  23. 23. Organizations still face basic pain points, ranging from confusion about Big Data to lack of skills 3 Big Data & Analytics North America | IBM Confidential Big Data and Analytics Challenges: 1. Adoption is still early as users are confused by what big data is 2. Organizations don’t have the skills to fully exploit it: a) Not having enough or the right IT skills to manage Big Data Projects b) Not having enough or the right analytics staff to analyze the data 3. Organizations lack the tools & integration to existing proprietary offering a) Unstructured or semi-structured text is difficult to query 4. There are underlying “information management” challenges that limit organizations ability to capitalize on big data Traditional relational databases / data warehouses not designed for new types of data 5. Trouble deciding what data is relevant (What data to keep store/discard) 6. Cost of technology infrastructure 7. Different sources of data (enterprise apps, web, search, video, mobile, social conversations and sensors) Source: IBM CEO,CIO, CFO, CMO Studies; Gartner Best Actions in a Decade of CIO Resolutions as CIOs Move From Technical Manager to Digital Leader, May 2013 , IDC Directions 2013: Building a Big Data and Analytics Road Map for Business Value Decem
  24. 24. World without secrets...
  25. 25. The rise of the Data Scientist in 2013 39 “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 Data Scientist: The Sexiest Job of the 21st Century – Harvard Business Review
  26. 26. CDO- Chief Data Officer role, one that reinforces the partnership among other C- suite executives and promotes establishing an Analytics Center of Excellence 40 Overall guidance and vision Chief Data Officer Managing the Enterprise program Working across the executive set Refining processes and introducing analytic innovation Guiding the Analytics Centers of Excellence Defining capabilities & technology investment * CDO backgrounds require experience in statistical analysis, marketing, finance, and/or operations  CDO role is two-fold: 1. Top executive responsible for business analytics strategy, guiding strategy team managing analytic priorities across all business units 2. In partnership with the CIO, guide IT infrastructure team with a centralized analytics platform  Must work closely with all C-Suite execs to ensure priorities are met and to facilitate cross-team collaboration and analytic skill  CDO is different from the CIO, functioning as key linkage between IT and Business  Includes relationships with CEO, CIO, CMO, CFO, and Lines of Business
  27. 27. CDO Responsibilities Working across the executive set to set strategy and define roadmap • Interfacing with CFO, CMO, COO and others to determine key business needs to tie analytics strategy to corporate strategy and how to execute and measure • Aligning teams, metrics framework and creation and maintenance of overall BA strategy • Defining value, prioritizing and creating the strategic and tactical roadmap of projects Overall guidance and vision to all analytic teams • Communications and evangelism of vision and roadmap • Coaching metric definition, model development targets, business case development and measurement of business outcomes • Managing pool of analytic skill that can assist, coach and enable teams Managing the enterprise vision • Program Management of all aspects of strategy, value, people, process and technology • Driving training, education and managing analytic skill advancement • Development of the advise and consult framework Guiding the Analytics Centers of Excellence • Creating the communication platform across teams (regular meetings, newsletters, collaboration, onboarding, knowledge share) • Defining organizational structures, dotted line structures, roles, responsibilities • Identifying stakeholders, gaps and assisting teams in increasing use of analytics Defining capabilities and technology solutions • Mapping capabilities to business needs • Assessing technology state and understanding gaps • Guiding technology investment and measuring TCO with IT team Refining processes and introducing innovative technology solutions • Assessing processes and understanding where analytics can refine process • Evaluating where continual improvements can be made to re-define process • Introduce analytic process that can enable and onboard satellite teams
  28. 28. 42 Customer service Marketing IT Operations Product development Human resources Finance Sales The CDO’s office— the Analytics Center of Excellence—will be the guiding, impartial team to work across various lines of business throughout an organization CDO & Analytics Center of Excellence
  29. 29. Como agir? 43 Funding Source of Value Sponsorship Data Platform Trust Culture Measurement Strategy Technology Organization Expertise Establish a common vision to guide actions and deliver value Create trustworthy relationships Create confidence with governance and security Ensure alignment between analytic focus and value creation Create value with rigor and collaboration Measure impact and model the future Make decision based on facts Increase knowledge-sharing opportunities Integrate hardware and software to manage big data Source: Analytics: A blueprint for value – Converting big data and analytics into results, IBM Institute for Business Value © 2013 IBM
  30. 30. Multiple Data Sources Prediction & Optimisation Models Organizational Transformation  Creatively source internal & external data  Upgrade IT architecture and infrastructure for easy merging of data  Focus on the biggest drivers of performance  Build models that balance complexity with ease of use  Create simple, understandable tools for people on the frontline.  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 1 2 3 Como agir?
  31. 31. Agir rapido, pois o futuro se torna passado rapidamente!
  32. 32. Cezar Taurion @ctaurion Facebook Linkedin