2013 csi interchange_pietro_leo - ex

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My Personal Introduction (light) to Big Data presented to the CSI Conference in Montpellier (France)

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2013 csi interchange_pietro_leo - ex

  1. 1. Big Data, the latest updates 1 Plenary session – 14 June 2013 Pietro Leo Executive Architect - IBM GBS Italy Big Data Analytics Leader Global Technology Progam Manager - IBM Academy of Technology Email: pietro_leo@it.ibm.com @pieroleo www.linkedin.com/in/pieroleo
  2. 2. @pieroleo www.linkedin.com/in/pieroleo BIOGRAPHY Pietro Leo Executive Architect - IBM GBS Italy Big Data Analytics Leader Global Technology Progam Manager - IBM Academy of Technology Email: pietro_leo@it.ibm.com @pieroleo www.linkedin.com/in/pieroleo Executive Analytics Architect with 20 years professional experience in Research & IT Services IBM Academy of Technology Core management Team Member and Global Technology Program Manager Extensive experience on Content Analytics, Big Data Analytics, Social Media Analytics, Knowledge Management, Knowledge and Data Integration, Very Large Mining and Search Engines, Semantic Search, Bioinformatics areas helping clients in complex (multi- millions) and mission-critical projects Technical leader as well as chief architect and scientist in a number of analytics projects whose overall effort size is over 150 years/man Social Business Passionate from disparate angles: Member of IBM Service Corps working in Ghana and strong #Socbiz and #innovation expert and #startup hunter Multidisciplinary education background: Higher artistic degree in Oboe, Computing science degree, Master of Science by Research degree in applied artificial intelligence, Master's degree in public funding management. Keynote speaker and author or co-author of more than 70 scientific and technical publications and and as well as co-author of two IBM books edited by IBM Readbooks. Received more than a dozen of IBM special awards for high technical achievements including also the mention into the IBM Corporate Technical Award Book 2010 edition, the IBM IT Architect Worldwide Technical Leadership Excellence Award in 2006 and the IBM Academy President's Award 2012.
  3. 3. @pieroleo www.linkedin.com/in/pieroleo Agenda Defining Big Data Big Data as a macro-trend and the State-of-the-Art The business impact of Big Data & Deep Dive on selected Big Data Experiences A Big Data IT Perspective Wrap-up & organizing for Big Data: Next “best action”
  4. 4. @pieroleo www.linkedin.com/in/pieroleo Measuring Big Data by using Big Data Source: Google Trends Big Data Business Intelligence Data Warehouse Business Analytics Correlated Query Terms
  5. 5. @pieroleo www.linkedin.com/in/pieroleo
  6. 6. @pieroleo www.linkedin.com/in/pieroleo Conventional Definitions of “Big Data” Never before possible Social Data Large volumes Unstructured Data Valuable insight, but difficult to extract Basically an ETL environment …..... These are partial and or wrong definitions
  7. 7. 7 @pieroleo www.linkedin.com/in/pieroleo Big Data enables us to see with new eyes....
  8. 8. 8 @pieroleo www.linkedin.com/in/pieroleo “The real voyage of discovery consists not in seeking new lands, but in seeing with new eyes....” Marcel Proust, A la recherche du temps perdu, 1913/27 Salvador Dalì - Impresiones de África y Afgano invisible con aparición sobre la playa del rostro de García Lorca en forma de frutero con tres higos, 1938 Dog Head Fruit Bowl Waterfall Table Bridge Dog Collar Dog Muzzel Hill Beach River Point of View 1Point of View 1 Point of View 2Point of View 2
  9. 9. 9 @pieroleo www.linkedin.com/in/pieroleo Big Data enables us to see with new eyes.... Salvador Dalì - Impresiones de África y Afgano invisible con aparición sobre la playa del rostro de García Lorca en forma de frutero con tres higos, 1938
  10. 10. @pieroleo www.linkedin.com/in/pieroleo 10 >80% Unstructured Data + External Data “Untouched” Data + Stream of Data Enterprise Data Machine Data People Data Big Data metaphor
  11. 11. @pieroleo www.linkedin.com/in/pieroleo Data is there and we need to make the best out of it
  12. 12. @pieroleo www.linkedin.com/in/pieroleo We produce and consume Data for a specific purpose
  13. 13. @pieroleo www.linkedin.com/in/pieroleo Source: A statue representing Janus Bifrons in the Vatican Museums Big Data as a new Business Concept and as a new Technology Concept
  14. 14. 14 @pieroleo www.linkedin.com/in/pieroleo Big Data as a new business concept: New values and opportunities for a number of stakeholders Chief Marketing Officer how to improve customer focus?...could predict the right offer for the right customer at the right time and improve customer value and intimacy or prevent churn? Chief Product Designer ...how we can innovste? … could we improve our product channels/design offering?? Chief Finance Officer ...could streamline compliance and understand risk exposure across businesses and regions? Chief Risk Officer ...uses anti fraud predictive analytics to detect and prevent rapid fire anomalous transactions or wire transfers identified as high probability of fraud? Chief Executive Officer ...could make better business decisions using accurate data across all company/system dimensions and across time horizons: past, present and future? Chief Information Officer ...could analyze oceans of machine generated logs to predict which components or equipment in the datacenter are likely to fail and thereby avert a disruption during critical quarter end? How we can support Zero high risks or manage crisis? Big Data Analytics
  15. 15. @pieroleo www.linkedin.com/in/pieroleo Big Data as a new technology concept: We need to combine internal and external data, utilized and under-utilized data, structured and unstructured data... and cross-link organization knowledge & data silos CRM • emails • claims • call center scripts • Chats with customers • … Transactional Info.: • Transactions • Orders • consultancies • … Legal Info: • Contracts • Complaints • Reports • Legal Actions • Fraud Data • … Knowledge Management •Manuals, wikis, couses •Projects Data •Market Analysis •RSS Business Feeds •Data feed: Bloomberg reuters • … IT Systems System Logs Application logs: web, vending machines, mobile Video Sensor Networks, RFID • … Social Media: • Global Social Networks: tweeter, facebook, etc. • Small communities: blogs, muros corporativos, • Internal Social Networks (employees) • News • … Big Data Analytics
  16. 16. @pieroleo www.linkedin.com/in/pieroleo Source: Cornell University - Maize kernal infected with Aspergillus flavus, which produced aflatoxin. http://www.plantpath.cornell.edu/labs/milgroom/Research_aflatoxin.html And http://www.special-clean.com/special- clean/en/mold/mold-lexicon-1.php For science, Big Data is the microscope of the 21st century
  17. 17. @pieroleo www.linkedin.com/in/pieroleo For Science, Big Data is the microscope of the 21st century Wine DNA Tracing
  18. 18. @pieroleo www.linkedin.com/in/pieroleo Just ONE Transaction path goes to the end in thousands and to complete that path tens of decision points were considered. Right now we store and analyze in our transactional systems just the end points: Buyer Fail! Fail! Fail! Fail Fail! Fail! Fail! Fail! Fail! Fail! Fail!Fail Fail! Fail! Fail! ….Win!!! Buying Decision Cloud Yes! For Business, Big Data is the answer and the need of the new emerging sub-transactional era
  19. 19. @pieroleo www.linkedin.com/in/pieroleo 19 Social Data from and about People Physical Sensors & Streams Terabytes to exabytes of existing data to process Streaming data, milliseconds to seconds to respond Structured, Semi- structured Unstructured, text & multimedia Uncertainty from inconsistency, ambiguities, etc. Volume Velocity Variety Veracity Data Content >80% <20% Traditional Enterprise Data Big data embodies new data characteristics created by today’s digitized marketplace Biological DNA Sequencers
  20. 20. @pieroleo www.linkedin.com/in/pieroleo 20 20 GlobalDataVolumeinExabytes Sensors (InternetofThings) Multiple sources: IDC,Cisco 100 90 80 70 60 50 40 30 20 10 AggregateUncertainty% VoIP 9000 8000 7000 6000 5000 4000 3000 2000 1000 0 2005 2010 2015 By 2015, 80% of all available data will be uncertain: Veracity Enterprise Data Data quality solutions exist for enterprise data like customer, product, and address data, but this is only a fraction of the total enterprise data. By 2015 the number of networked devices will be double the entire global population. All sensor data has uncertainty. Social Media (video, audio and text) The total number of social media accounts exceeds the entire global population. This data is highly uncertain in both its expression and content.
  21. 21. @pieroleo www.linkedin.com/in/pieroleo “Big Data is the set of technical capabilities, management processes and skills for converting vast, fast, and varied data into Right Data to produce useful knowledge” Source: Definition discussed during the work of the Word Summit on Big Data and Organization Design Paris – 2013 and Adapted from: Beacon Report – Big Data Big Brains – 2013 In summary, what is Big Data?
  22. 22. @pieroleo www.linkedin.com/in/pieroleo What is New and Different? A lot more data and different kinds of data. Historically most data was structured data – rows and columns Today it is unstructured data like aerial photos, audio from call centers, video from surveillance cameras, e- mails, texts, diagrams. A shift in focus from data stocks to data flows. Historical information was stored in data warehouses and analyzed by data mining. Streaming data arrives in real time allowing us to influence events as they happen. We can prevent some bad events from ever happening at all. Shift in the power structure of the company. Many companies have analog establishments. We need to shift power to those who can draw valuable insights from data and analytics and implement them. Shift from periodic to real time or continuous decision making. We need an increase in the clock speed of every process in the company. There is a potential for “Big Data” to become a fundamental center for the company. Is it a new dimension of structure? Organization Design IssuesTechnology Issues Source: Jay R. Galbraith, from Word Summit on Big Data and Organization Design Paris – 2013
  23. 23. @pieroleo www.linkedin.com/in/pieroleo Agenda Defining Big Data Big Data as a macro-trend and the State-of-the-Art The business impact of Big Data & Deep Dive on selected Big Data Experiences A Big Data IT Perspective Wrap-up & organizing for Big Data: Next “best action”
  24. 24. @pieroleo www.linkedin.com/in/pieroleo IBM Institute for Business Value and the Saïd Business School partnered to benchmark global big data activities 24 IBM Global Business Services, through the IBM Institute for Business Value, develops fact-based strategies and insights for senior executives around critical public and private sector issues. Saïd Business School University of Oxford IBM Institute for Business Value The Saïd Business School is one of the leading business schools in the UK. The School is establishing a new model for business education by being deeply embedded in the University of Oxford, a world-class university, and tackling some of the challenges the world is encountering. www.ibm.com/2012bigdatastudy
  25. 25. @pieroleo www.linkedin.com/in/pieroleo Big Data Analytics has evolved from business initiative to business imperative 63% 58% 37% 2012 2011 2010 70% increase Source: 1 2010 and 2011 datasets © Massachusetts Institute of Technology. 2 Analytics: The real-world use of big data. 2012 Study conducted by IBM Institute for Business Value, in collaboration with Säid Business School at the University of Oxford. 3.6x Likelihood of organizations competing on analytics to outperform their peers2 Percentage of respondents who cited a competitive advantage from the use of information and analytics1,2
  26. 26. @pieroleo www.linkedin.com/in/pieroleo Three out of four organizations have big data activities underway; and one in four are either in pilot or production 26 Total respondents n = 1061 Totals do not equal 100% due to rounding Big data activities Respondents were asked to describe the state of big data activities within their organization. Early days of big data era  Almost half of all organizations surveyed report active discussions about big data plans  Big data has moved out of IT and into business discussions Getting underway  More than a quarter of organizations have active big data pilots or implementations  Tapping into big data is becoming real Acceleration ahead  The number of active pilots underway suggests big data implementations will rise exponentially in the next few years  Once foundational technologies are installed, use spreads quickly across the organization
  27. 27. @pieroleo www.linkedin.com/in/pieroleo Five key findings highlight how organizations are moving forward with big data 27 Big data is dependent upon a scalable and extensible information foundation2 The emerging pattern of big data adoption is focused upon delivering measureable business value5 Customer analytics are driving big data initiatives1 Big data requires strong analytics capabilities4 Initial big data efforts are focused on gaining insights from existing and new sources of internal data3
  28. 28. @pieroleo www.linkedin.com/in/pieroleo Key Findings: Customer analytics are driving Big Data initiatives Big data Infrastructure Big data Sources Analytics capabilitiesTotal respondents n = 1061 Big data objectives Top functional objectives identified by organizations with active big data pilots or implementations. Responses have been weighted and aggregated. Customer-centric outcomes Operational optimization Risk / financial management New business model Employee collaboration Big Data areas of work
  29. 29. @pieroleo www.linkedin.com/in/pieroleo Big data leadership shifts from IT to business as organizations move through the adoption stages 29 CIOs lead early efforts  Early stages are driven by CIOs once leadership takes hold to drive exploration  CIOs drive the development of the vision, strategy and approach to big data within most organizations  Groups of business executives usually guide the transition from strategy to proofs of concept or pilots Business executives drive action  Pilot and implementation stages are driven by business executives – either a function-specific executive such as CMO or CFO, or by the CEO  Later stages are more often centered on a single executive rather than a group; a single driving force who can make things happen is critical Leadership shifts Respondents were asked which executive is most closely aligned with the mandate to use big data within their organization. Box placement reflects the degree to which each executive is dominant in a given stage. Total respondents n = 1028
  30. 30. @pieroleo www.linkedin.com/in/pieroleo Agenda Defining Big Data Big Data as a macro-trend and the State-of-the-Art The business impact of Big Data & Deep Dive on selected Big Data Experiences A Big Data IT Perspective Wrap-up & organizing for Big Data: Next “best action”
  31. 31. @pieroleo www.linkedin.com/in/pieroleo Utilities  Weather impact analysis on power generation  Transmission monitoring  Smart grid management Retail  360° View of the Customer  Click-stream analysis  Real-time promotions Law Enforcement  Real-time multimodal surveillance  Situational awareness  Cyber security detection Transportation  Weather and traffic impact on logistics and fuel consumption  Traffic congestion Financial Services  Fraud detection  Risk management  360° View of the Customer IT  System log analysis  Cybersecurity Telecommunications  CDR processing  Churn prediction  Geomapping / marketing  Network monitoring What can you do with Big Data? Health & Life Sciences Epidemic early warning ICU monitoring Remote healthcare monitoring
  32. 32. @pieroleo www.linkedin.com/in/pieroleo • Advanced client segmentation • Leveraging customer sentiment analysis • Reducing customer churn • Optimizing the supply chain • Deploying predictive maintenance capabilities • Transform threat & fraud identification processes Operations • Enabling rolling plan, forecasting and budgeting • Automating the financial close process • Delivering real-time dashboards Finance • Making risk-aware decisions • Managing financial and operational risks • Reducing the cost of compliance Risk Examples: Customers / Clients Another perspective: let's focus on ROI in core business areas for Big Data • Advanced client segmentation • Leveraging customer sentiment/opinion analysis • Reducing customer churn
  33. 33. @pieroleo www.linkedin.com/in/pieroleo Big Data for Customer Analytics challenge: build a 360°Integrated Customer View … and more! SINGLE VIEW Business Data, Social Data, Interactive data 360°Integrated Customer View Marketing Cust. Care Sales Risk, Fraud Customers / Clients
  34. 34. @pieroleo www.linkedin.com/in/pieroleo Big Data for Customer Analytics challenge: build a 360°Integrated Customer View … and more SINGLE VIEW Business Data, Social Data, Interactive data 360°Integrated Customer View Marketing Cust. Care Sales Risk, Fraud Customers / Clients How?How?Why?Why? Who?Who? What?What?
  35. 35. @pieroleo www.linkedin.com/in/pieroleo Big Data for Customer Analytics challenge: build a 360°Integrated Customer View … and more 360°Integrated Customer View Customers / Clients How?How?Why?Why? Who?Who? What?What? Project Example 1 TV Broadcaster Project Example 2 Media and Entertainment Project Example 3 Hair care manufacturer Big Data Analytics Project Space
  36. 36. @pieroleo www.linkedin.com/in/pieroleo36 • Social media analysis is a new and increasingly relevant way to become more competitive in consumer-driven markets. Mediaset wanted to increase its market share as well as launch new services and digital-content distribution. s marketing campaigns and better • Television content and services are becoming increasingly consumer driven, and the media outlet that can capture and use customer sentiment to its benefit gains a competitive advantage. This media provider in Italy applied an advanced analytics solution to analyze more than 1.6 million unstructured data points from Web 2.0 sources to gain an understanding of its customers’ attitudes, opinions and preferences. Challenge Benefits Solution Customer Quote “Big data is a great opportunity for TV innovation in the next years. TV viewing is transforming into a multiplatform and participative experience; the better we know and understand our viewers, the better we can serve them”. 36 A TV broadcaster analysed Big Data Analytics to collect Customer longitudinal point of views from Web 2.0 and correlate them with internal data • Television content and services are becoming increasingly consumer driven, and the media outlet that can capture and use customer sentiment to its benefit gains a competitive advantage. This media provider in Italy applied an advanced analytics solution to analyze more than 1.6 million unstructured data points from Web 2.0 sources to gain an understanding of its customers’ attitudes, opinions and preferences. • Analyzed more than 1.6 million data points on social media outlets to discover public sentiment and correlations with customer satisfaction • Helped Mediaset to discover and measure viewer sentiments expressed in Web 2.0 contents related to its TV contents and ad campaigns
  37. 37. @pieroleo www.linkedin.com/in/pieroleo Big Data Analytics to expand knowledge about customer profiles and measuring marketing campaign • Analysis of social media messages for large Media and Entertainment company to determine reaction to movie commercials aired during the SuperBowl • Insights based on 30M+ social media consumer profiles created by analyzing over a Billion messages • Real-time evolution of insights correlated with the airing of the commercial • Analysis of social media messages for large Media and Entertainment company to determine reaction to movie commercials aired during the SuperBowl • Insights based on 30M+ social media consumer profiles created by analyzing over a Billion messages • Real-time evolution of insights correlated with the airing of the commercial Key Business Questions: How many people are talking about the film ? • Intention to see the movie, Impact of SuperBowl commercial Who are they ? • Demographics, Influencers, avid movie goers What is the reaction ? • Categorized sentiment (plot, characters, …) • Comparison with competitive movies Key Business Questions: How many people are talking about the film ? • Intention to see the movie, Impact of SuperBowl commercial Who are they ? • Demographics, Influencers, avid movie goers What is the reaction ? • Categorized sentiment (plot, characters, …) • Comparison with competitive movies Jan 1 5pm 6pm 7pm 8pm Super Bowl Monitoring Period Feb 5th Golden Globes NFC Championship 9pm 10pm 11pm • Buzz and sentiment • Gender, Location and Occupation • Avid movie-goers, comic book fans • Intent to see specific films • Specific attributes of the film/trailer
  38. 38. @pieroleo www.linkedin.com/in/pieroleo ■ Their earlier analysis of Google search requests suggested that hair problems formed a significant part of what consumers care about… ■ … but Big Data Analytics showed that people rarely chatted about their hair problems when discussing and comparing hair care products The marketing messages were re-focused in line with this more nuanced insight – promoting what customers want for their hair to harmonize with the social media agenda On another perspective an Hair care manufacturer finds out what consumers really chat about
  39. 39. @pieroleo www.linkedin.com/in/pieroleo 360-degree Consumer Profiles from Social Media Personal Attributes • Identifiers: name, address, age, gender, occupation… • Interests: sports, pets, cuisine… • Life Cycle Status: marital, parental Personal Attributes • Identifiers: name, address, age, gender, occupation… • Interests: sports, pets, cuisine… • Life Cycle Status: marital, parental Products Interests • Personal preferences of products • Product Purchase history • Suggestions on products & services Products Interests • Personal preferences of products • Product Purchase history • Suggestions on products & services Life Events • Life-changing events: relocation, having a baby, getting married, getting divorced, buying a house… Life Events • Life-changing events: relocation, having a baby, getting married, getting divorced, buying a house… Monetizable intent to buy products Life Events Location announcements Intent to buy a house I'm thinking about buying a home in Buckingham Estates per a recommendation. Anyone have advice on that area? #atx #austinrealestate #austin I'm thinking about buying a home in Buckingham Estates per a recommendation. Anyone have advice on that area? #atx #austinrealestate #austin Looks like we'll be moving to New Orleans sooner than I thought. Looks like we'll be moving to New Orleans sooner than I thought. College: Off to Stanford for my MBA! Bbye chicago! College: Off to Stanford for my MBA! Bbye chicago! I'm at Starbucks Parque Tezontle http://4sq.com/fYReSj I'm at Starbucks Parque Tezontle http://4sq.com/fYReSj I need a new digital camera for my food pictures, any recommendations around 300? I need a new digital camera for my food pictures, any recommendations around 300? What should I buy?? A mini laptop with Windows 7 OR a Apple MacBook!??! What should I buy?? A mini laptop with Windows 7 OR a Apple MacBook!??! Timely Insights • Intent to buy various products • Current Location • Sentiment on products, services, campaigns • Incidents damaging reputation • Customer satisfaction/attrition Timely Insights • Intent to buy various products • Current Location • Sentiment on products, services, campaigns • Incidents damaging reputation • Customer satisfaction/attrition Relationships • Personal relationships: family, friends and roommates… • Business relationships: co-workers and work/interest network… Relationships • Personal relationships: family, friends and roommates… • Business relationships: co-workers and work/interest network…
  40. 40. @pieroleo www.linkedin.com/in/pieroleo40 AMEX Example: Business Models based on connecting Virtual and Real Worlds American Express Smart Offer A portal that collects special offers and discounts from retailers and detail about the customer segment that is target Marketing segmentation engine that evaluate customer profiles and select the best coupon to propose Moble app and connection with Twitter, Facebook e Foursquare to communicate with the customers and enable viral effects Just virtual Coupons are managed! Customers activate the coupon and receive on montly basis on the credit card account the equivalent of the coupon discounts after that transactions were registred API
  41. 41. @pieroleo www.linkedin.com/in/pieroleo41 What Data AMEX Sync acquires from Facebook, Twitter e Foursquare? New CRM Data... American Express Smart Offer
  42. 42. @pieroleo www.linkedin.com/in/pieroleo Twitter Inc. is experimenting with becoming a shopping mall. Twitter and American Express Co. said Monday they struck a partnership to allow Twitter users to buy products for the first time directly on the short messaging service. American Express card holders who connect their card numbers to their Twitter accounts can post on Twitter to trigger a purchase of select products, including discounted American Express gift cards, Kindle Fire tablets from Amazon.com Inc. and jewelry from designer Donna Karan. The program will roll out over the next few days. The arrangement hints at a potential new source of revenue for Twitter, which has largely been reliant on advertising for revenue. Neither Amex nor Twitter will discuss financial terms of their partnership, but Twitter wouldn’t rule out taking a cut of future e-commerce sales. The American Express partnership also is a way for Twitter to prove the link between marketing activity on Twitter and a ringing cash register. API - Services Twitter, Amex Launch Pay-By-Tweet Service Source: http://blogs.wsj.com/digits/2013/02/11/twitter-amex-to-collaborate-on-e-commerce-sales-on-twitter/
  43. 43. @pieroleo www.linkedin.com/in/pieroleo external traits intrinsic traits Omni Profile of each individual …..Further Hyper- Personalized 360°Integrated Customer View + Personality Opennes Conscientiousness Extraversion Agreeableness Neuroticism Perception Fundamental needs Ideal Liberty Love Structure Social behavior Responsiveness Temporal patterns of activities Social relationships to others Similarity Tie strength Frequency Recency Intensity Reciprocity Intimacy Big Data for Customer Analytics challenge: build a 360°Integrated Customer View … and more! Customers / Clients
  44. 44. @pieroleo www.linkedin.com/in/pieroleo Big Data enabled doctors from University of Ontario to apply neonatal infant monitoring to predict infection in ICU 24 hours in advance Performing real-time analytics using physiological data from neonatal babies Continuously correlates data from medical monitors to detect subtle changes and alert hospital staff sooner Early warning gives caregivers the ability to proactively deal with complications “Customer Analytics” in some Industry means safe life
  45. 45. @pieroleo www.linkedin.com/in/pieroleo Agenda Defining Big Data Big Data as a macro-trend and the State-of-the-Art The business impact of Big Data & Deep Dive on selected Big Data Experiences A Big Data IT Perspective Wrap-up & organizing for Big Data: Next “best action”
  46. 46. @pieroleo www.linkedin.com/in/pieroleo Data Warehouse Operational Analytics Structured, analytical, logical Big Data Ad Hoc Analytics Creative, holistic thought, intuition Unstructured Exploratory Iterative Brand sentiment Product strategy Maximum asset utilization Structured Repeatable Linear Monthly sales reports Profitability analysis Customer surveys Big Data IT Perspective: augmenting traditional IT investments
  47. 47. @pieroleo www.linkedin.com/in/pieroleo Manage & store huge volume of any data Hadoop File System MapReduce Manage Streaming Data Stream Computing Analyze Unstructured Data Text Analytics Engine Data WarehousingStructure and control data Integrate and govern all data sources Integration, Data Quality, Security, Lifecycle Management, MDM Understand and navigate federated big data sources Federated Discovery and Navigation From an IT perspective leveraging Big Data and Big Data Analytics requires multiple platform capabilities
  48. 48. @pieroleo www.linkedin.com/in/pieroleo BI / Reporting Exploration / Visualization Functional App Industry App Predictive Analytics Content Analytics Analytic Applications IBM Big Data Platform Systems Management Application Developmen t Accelerators Big Insights Volume, Variety Cost-effectively process and analyze any type of data Visualization & Discovery Visibility Understand, find, and navigate federated big data Data Warehouse Volume, Structured Purpose-built offerings High-performance appliances and software Information Integration & Governance Veracity Trusted information Parallel processing for high-volume integration Best practices Stream Computing Building a Big Data Platform: The IBM perspective Velocity Analyze data-in-motion to produce insights in micro-seconds Agile, multi-tenant shared infrastructure BIG Performance Option of an optimized low-latency MapReduce implementation fully compatible with open- source Hadoop
  49. 49. @pieroleo www.linkedin.com/in/pieroleo Agenda Defining Big Data Big Data as a macro-trend and the State-of-the-Art The business impact of Big Data & Deep Dive on selected Big Data Experiences A Big Data IT Perspective Wrap-up & organizing for Big Data: Next “best action”
  50. 50. @pieroleo www.linkedin.com/in/pieroleo Business-centric Big Data enables you to start with a critical business pain and expand the foundation for future requirements.... start with the most critical one!
  51. 51. @pieroleo www.linkedin.com/in/pieroleo 51 Using twitter?  Dear delegate, we value the feedback provided through feedback forms, but we would like to encourage you to use the twitter hashtag #IBMCSII for your: Findings on the event Logistics Suggestions Network diner Speakers Content Weather ... @pieroleo www.linkedin.com/in/pieroleo You can find me here:
  52. 52. @pieroleo www.linkedin.com/in/pieroleo Grazie! Pietro Leo Executive Architect - IBM GBS Italy Big Data Analytics Leader Global Technology Progam Manager - IBM Academy of Technology Email: pietro_leo@it.ibm.com @pieroleo www.linkedin.com/in/pieroleo
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