IBM Big Data Platform

Transcript

1 IBM Big Data Platform Turning big data into smarter decisions Silvia Cesati Infosphere team leader IBM Software Group June 17, 2013

2 La Nuova Metafora: Big Data >80% Unstructured Data Untouched Data + External Data + Stream of Data Enterprise Data Machine Data People Data 2 2

3 le informazioni sono il nuovo petrolio? Big Data has arrived at Seton Health Care Family, fortunately accompanied by an analytics tool that will help deal with the complexity of more than two million patient contacts a year Data is the new oil. Clive Humby Companies are being inundated with data from information on customer-buying habits to supply-chain efficiency. But many managers struggle to make sense of the numbers. At the World Economic Forum last month in Davos, Switzerland, Big Data was a marquee topic. A report by the forum, Big Data, Big Impact, declared data a new class of economic asset, like currency or gold. now Watson is being put to work digesting millions of pages of research, incorporating the best clinical practices and monitoring the outcomes to assist physicians in treating cancer patients. Increasingly, businesses are applying analytics to social media such as Facebook and Twitter, as well as to product review websites, to try to understand where customers are, what makes them tick and what they want, says Deepak Advani, who heads IBM s predictive analytics group. The Oscar Senti-meter a tool developed by the L.A. Times, IBM and the USC Annenberg Innovation Lab analyzes opinions about the Academy Awards race shared in millions of public messages on Twitter. 3

4 Immagina di poter sfruttare tutte le Risorse Dati... In Ogni Settore Analisi da ore a 70 Millisecondi Efficienza della distribuzione 10 PB in pochi minuti Diagnosi con 24 ore di anticipo 80% di riduzione dei tempi per ottimizzazione inventario Analisi sui dati di borsa da 26 ore a 2 minuti su 2 PB Analisi real time dati telefonici Riduzione costi hw del 90% 4

5 Applicazioni Big Data Analisi cosa si dice sui Social Media di un argomento Analisi messaggi Call Center Analisi dei LOG. Identificazione delle frodi. Ricercare dati attraverso un motore federato Analisi di dati provenienti da sensori... Si ricorre ad una soluzione Big Data, ad esempio, quando: - risulta necessario analizzare TUTTI i dati potenzialmente disponibili e quando l elaborazione di un loro campione non sarebbe significativa e in grado di fornire risultati efficaci. - si vuole ESPLORARE, anche in modo interattivo, i dati disponibili nei casi in cui le misure e gli indicatori di business non siano predeterminati. - occorre analizzare un FLUSSO CONTINUO ed ampio di dati per prendere decisioni in tempo reale Il fenomeno Big Data non è legato ad un particolare settore di industria fa leva sulla crescita del volume dei dati e su ulteriori dimensioni come la Velocità e la Varietà dei dati disponibili. 5

6 Le caratteristiche del Big Data Cost efficiently processing the growing Volume 50x 35 ZB Responding to the increasing Velocity 30 Billion RFID sensors and counting Collectively analyzing the broadening Variety 80% of the worlds data is unstructured Establishing the Veracity of big data sources 1 in 3 business leaders don t trust the information they use to make decisions 6

7 Occorre andare oltre l approccio tradizionale della gestione dei dati Transactional and Application Data Machine Data Social Data Enterprise Content Volume Velocity Variety Variety Structured Semi-structured Highly unstructured Highly unstructured Throughput Ingestion Veracity Volume 7

8 La possibilità di analizzare tutti I dati rende le informazioni non solo il nuovo petrolio..ma la nuova moneta di scambio! Cost effectively manage and analyze all available data in its native form unstructured, structured, streaming Website Social Media Billing ERP CRM RFID Network Switches 8

9 Clients Achieve Breakthrough Outcomes With IBM s Big Data Platform Imperative Primary Capability Business Value Run Zero Latency Operations InfoSphere Data Explorer Streamlined support and operations by providing visibility to over 30 data repositories Run Zero Latency Operations InfoSphere BigInsights Reduce maintenance costs and differentiate by optimal turbine placement Know Everything about your Customers InfoSphere Streams Analyzed call records to drive real-time promotions & reduce churn Exploit Instrumented Assets IBM Netezza Increased network availability by identifying and fixing holes Instant Awareness of Risk and Fraud IBM Netezza Analysis time on 2 PB of data cut from 26 hours to 2 minutes 9

10 Entry Points are Accelerated by Products Within the Big Data Platform 1 Unlock Big Data InfoSphere Data Explorer 2 Analyze Raw Data InfoSphere BigInsights Analytic Applications BI / Exploration / Functional Industry Predictive Reporting Visualization App App Analytics Visualization & Discovery IBM Big Data Platform Application Development Accelerators Content BI / Analytics Reportin g Systems Management 3 Simplify your warehouse IBM Warehouse Solutions Hadoop System Stream Computing Data Warehouse 4 Reduce costs with Hadoop InfoSphere BigInsights Information Integration & Governance 5 Analyze Streaming Data InfoSphere Streams 10

11 1 Unlock Big Data: Proctor and Gamble Customer Need Understand existing data sources Expose the data within existing content management and file systems for new uses, without copying the data to a central location Search and navigate big data from federated sources Value Statement Get up and running quickly and discover and retrieve relevant big data Use big data sources in new information-centric applications Customer examples Proctor and Gamble Connect employees with a 360 view of big data sources Get started with: InfoSphere Data Explorer 11

12 5 Streaming Data: Ufone Customer Need Harness and process streaming data sources Select valuable data and insights to be stored for further processing Quickly process and analyze perishable data, and take timely action Value Statement Significantly reduced processing time and cost process and then store what s valuable React in real-time to capture opportunities before they expire Streaming Data Sources Streams Computing ACTION Customer examples Ufone Telco Call Detail Record (CDR) analytics for customer churn prevention Get started with: InfoSphere Streams 12

13 3 catalina marketing Customer Need Improve general-purpose data warehouse performance optimize queries that take hours to run Enterprise data warehouse is encumbered by too much data for too many purposes Ability to ingest huge volumes of structured data and run multiple concurrent deep analytic queries Value Statement Speed x faster performance on deep analytics Simplicity minimal administration and tuning of the appliance Integrated, workload-optimized systems; get up and running quickly Customer examples Catalina Marketing executing 10x the amount of predictive workloads with the same staff Get started with: IBM PureData, Smart Analytics System, InfoSphere Warehouse 13

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