1、数据资本的崛起数据资本的崛起The Rise Of Data Capital21Copyright 2015,Oracle and/or its affiliates.All rights reserved.|2Safe Harbor StatementThe following is intended to outline our general product direction.It is intended for information purposes only,and may not be incorporated into any contract.It is not a com
2、mitment to deliver any material,code,or functionality,and should not be relied upon in making purchasing decisions.The development,release,and timing of any features or functionality described for Oracles products remains at the sole discretion of Oracle.2018年大数据博览峰会主题年大数据博览峰会主题 数据创造价值，创新驱动未来数据创造价值，
3、创新驱动未来 Data Creates Value,Innovation Drives the Future 年度主题：数字经济推动新的增长年度主题：数字经济推动新的增长 The Theme of the Year:Digital Economy Drives New Growth32018 Big Data Expo Summit Theme24Copyright 2015,Oracle and/or its affiliates.All rights reserved.|应用案例Use Cases推动创新推动创新Drive Innovation客户洞察客户洞察Customer Insigh
4、t运营效率运营效率Operational Efficiency欺诈风险与合规欺诈风险与合规Fraud Risk&ComplianceCopyright 2017,Oracle and/or its affiliates.All rights reserved.|Confidential Oracle Internal/Restricted/Highly RestrictedCopyright 2017,Oracle and/or its affiliates.All rights reserved.|Reduced time spent between client engagement le
5、ading to increased revenue stream and forecasting accuracy智能智能应用国际应用国际改善非洲医疗卫生服务改善非洲医疗卫生服务40%通过易于使用的仪表板节省了30以上的工作时间和精力，为新的医疗保险提供商和医疗保健机构提供支持，让他们无需每次重新创建和重新配置客户的设置 为保险公司提供准确和及时的数据，来创建相关的医疗保险产品节省和客户之间的过程时间从而增加收入来源和销售预测准确性Copyright 2018,Oracle and/or its affiliates.All rights reserved.|Confidential Ora
6、cle Internal/Restricted/Highly Restricted6Copyright 2017,Oracle and/or its affiliates.All rights reserved.|35,000每天节省呼叫中心工作的分钟数Call center minutes saved daily改善网络分析，呼叫中心效改善网络分析，呼叫中心效率率 优化用户和网络数据处理 加强分析和报告 改善客户服务代理响应时间 部署的Oracle大数据机和ISV合作伙伴mCentric的应用程序“没有其他能提供这种性能的平台.”Globacom有限公司集团首席运营官Jameel Moham
7、med40 x 加速 Faster 网络事件分析network event analysisCopyright 2018,Oracle and/or its affiliates.All rights reserved.|加速产品测试加速产品测试Accelerate Product Testing 管理和分发来自7000多个传感器的数据，每次测试2 TB。对多个团队的快速并发访问缩短了分析时间，并为后续测试实现了快速周转30%缩短测试周期，加快上市时间Reduction in test time which accelerates time to market7Manage and distr
8、ibute data from over 7,000 sensors,2 TB per test.Rapid,concurrent access to multiple teams shortens analysis time and enables rapid turnaround for subsequent tests Copyright 2018,Oracle and/or its affiliates.All rights reserved.|Oracle Confidential Internal/Restricted/Highly Restricted8Path to conve
9、rsionMix and effectivenessMeasuring ROIAttribution优化全渠道体验优化全渠道体验Optimize the omni-channel experience 每年为100万乘客提供相关消息，内容和图像通过网站，电子邮件和房间传单渠道进行测试，定位和个性化促销超过40的转换率，提升交叉销售和服务的增加销售7%-10%收入增加收入增加increase in revenuesThe NHSBSA Data Analytics Story英国国民卫生保健体系商务署英国国民卫生保健体系商务署数据分析项目数据分析项目Abigail Giles-Haigh 高级数
10、据科学家 NHS Business Services Authority2015/16 交易交易1,077,678,779十亿处方药项目处理十亿处方药项目处理Prescriptions items processed2.8 million 处方药预付认证处方药预付认证43,528,383FP17 处理的牙齿理赔处理的牙齿理赔3.6 millionEHIC 应用应用33 billion经过处理的资金经过处理的资金The amount of money that flows through our books449,113NHS完成的养老金完成的养老金案例案例We will derive insi
11、ght from data to drive change3,509,394处理的电话处理的电话prescription prepayment certificates distributedThe number of cases completed in NHS PensionsThe number of calls our Contact Centre handled挑战挑战The ChallengeNHSBSA asked to collaborate to deliver 1bn of annual recurring savings by March 2018寻找和评估节省的机会Fi
12、nding and sizing the opportunities to make savings答案答案The answer从我们在系统中所掌握的数据中驱动洞察 Driving insight from the data we hold in operational systems技术使我们能够将所有数据放到一个环境中并分析而不影响操作Technology that would enable us put all our data into one environment and analyse it without impacting operations技术保证如果我们问有关大容量的数
13、据问题时不会出现问题Technology that would not turn off the lights if we asked a question of large volumes of data一个团队有人可以照顾的数据,做艰苦的处理,然后展现发现A team of people who could look after the data,do the hard sums and then present the findingsWe will derive insight from data to drive change收益收益 The outcome使用 Oracle 工程化
14、系统创建数据实验室Creation of a data lab using Oracle engineered system专门的分析人员、数据科学家和统计学家团队Dedicated team of analysts,data scientists and statisticiansWe will derive insight from data to drive change在前2年内发现的潜在节省超过8.35亿欧元 Over 835m of potential savings identified within first 2 yearsOracle ROI 奖Oracle ROI awa
15、rd Copyright 2018,Oracle and/or its affiliates.All rights reserved.|ConfidentialBIDA Data Analytics Platform&Project DeliveryBIDA 分析平台分析平台&项目实施项目实施美国财富100强能源公司，营收约335亿美元AMERICAN FORTUNE 100 ENERGY COMPANYIT GENERATES REVENUES OF APPROXIMATELY$33.5 BILLION Copyright 2016,Oracle and/or its affiliates.
16、All rights reserved.|智慧能源服务的一组相关数字Oracle and Erste Group Confidential14IT BIDA DAP Smart Energy Services“By the Numbers6,200 Terabytes数据分析平台所有层的可用容量（数据分析平台所有层的可用容量（DAP）Available capacity in data analytics platform all tiers(DAP)72高峰期高峰期IT项目团队资源项目团队资源Peak IT Project Team Resources7供应商交付合作伙伴供应商交付合作伙伴V
17、endor Delivery Partners13在数据建模，映射和摄入来填充DAP过程中的不同步骤Distinct Steps in Data Modeling,Mapping and Ingestion Process to Populate the DAP7,650来自来自33个生产源系统的个生产源系统的数据属性数据属性Data Attributes from 33 Production Source Systems 1,600业务规则将在业务规则将在IT数据集成中进行分析和数据集成中进行分析和/或开发或开发Business Rules to be analyzed and/or dev
18、eloped in IT data integrations12应用新技术包括应用新技术包括Hadoop，Scoop，Impala，Oracle Analytics，Spark，Hive，大数据，大数据SQL，Scala，Oracle R，大数据设备，大数据设备，Oracle Data Integrator和和Oracle融合中间件融合中间件New Technologies including Hadoop,Scoop,Impala,Oracle Analytics,Spark,Hive,Big Data SQL,Scala,Oracle R,Big Data Appliances,Oracl
19、e Data Integrator and Oracle Fusion Middleware内部分析应用程序内部分析应用程序 Internal Analytics ApplicationInternal Analytics Application数据分析平台数据分析平台 Data Analytics PlatformData Analytics Platform跨域的跨域的BIDA参考架构参考架构 Cross-Domain BIDA Reference Architecture数据源数据源Data SourcesData Sources数据集成数据集成 Data IntegrationData
20、 IntegrationDatabase Connectivity/ReplicationManaged File TransferExtract&LoadData Validation 数据湖数据湖Data LakeData LakeDistributed/Batch ProcessingDistributed File SystemIndex&SearchFast Data AccessPower SandboxData StagingActive ArchivingAnalytics Processing(Data Discovery,Machine Learning)Transform
21、ation结构化数据存储结构化数据存储Structured Data StoresStructured Data StoresStructured Data MartColumnar/MPP Data Store支持基础设施组件支持基础设施组件 Supporting Infrastructure ComponentsSupporting Infrastructure ComponentsSecurityMeta Data ManagementBackup/Data RecoveryMonitoring&ManagementSchedulingGovernance数据交换数据交换 Data Ex
22、changeData Exchange外部分析应用外部分析应用 External Analytics ApplicationExternal Analytics ApplicationBI&ReportingData DiscoveryVisualizationAnalytics(Predictive/Prescriptive)InternInternalalExternExternalalWeb ServicesBatch TransferJDBC/ODBC ConnectorSQL InterfaceDistributed Query15实时数据交换实时数据交换Real-time Data
23、 ExchangeReal-time Data Exchange流流处处理理 Stream processingStream processingBusiness rulesEvent processingContinuous QueryReal-time/streaming analyticsBI&ReportingVisualizationAnalytics(Predictive/Prescriptive)Real-time/streaming analytics以硬件为中心的解决方案Hardware-centric solutions内部软件为中心的解决方案Internal softwa
24、re-centric solutions特定领域的供应商和解决方案Domain-specific vendors&solutionsOracle PULA合同可用于突出显示在红色和蓝色框中的功能。The Oracle PULA contract could be leveraged for capabilities highlighted in the red and blue boxes.BIDA参考架构的收益参考架构的收益 16Benefits of BIDA Reference ArchitectureBIDABIDA核心能力核心能力Key Capabilities of BIDA Ar
25、chitectureKey Capabilities of BIDA Architecture数据集成层数据集成层Data Integration Layer数据湖数据湖Data Lake数据交换层数据交换层Data Exchange Layer内部报告和分析内部报告和分析Internal Reporting&Analytics外部供应商分析应用程序外部供应商分析应用程序External Vendor Analytics Applications12345收益收益/价值价值 Benefits/ValueBenefits/Value通过通过ExelonExelon数据科学家实现内部分析和报告，并
26、为所有运营公司的供应数据科学家实现内部分析和报告，并为所有运营公司的供应商分析提供数据交换。商分析提供数据交换。Enables internal analytics and reporting by Exelon data scientists and provides data exchange for vendor analytics for all operating companies.除分析和报告外，通用的内部除分析和报告外，通用的内部BIDABIDA架构还标准化了提供内部和外部数据架构还标准化了提供内部和外部数据交换，应用程序和外部供应商的集成层交换，应用程序和外部供应商的集成层I
27、n addition to analytics and reporting,a common internal BIDA architecture enables a standardized integration layer for internal and external data exchanges,applications and external vendor 外部供应商和内部数据和分析解决方案解耦，从而能灵活地修改，添加外部供应商和内部数据和分析解决方案解耦，从而能灵活地修改，添加或更改供应商分析合作伙伴。或更改供应商分析合作伙伴。De-couples external ven
28、dor and internal data and analytics solutions,allowing for flexibility in modifying,adding or changing vendor analytics partners.我们的我们的BIDABIDA架构路线图将通过提供不属于外部分析供应商范围的通用数架构路线图将通过提供不属于外部分析供应商范围的通用数据存储库（即数据湖）来整合嵌入到各个实用程序中的数据仓库孤岛。据存储库（即数据湖）来整合嵌入到各个实用程序中的数据仓库孤岛。Our BIDA Architecture Roadmap will consolid
29、ate data warehouse silos embedded in the individual utilities by delivering a common data repository(i.e.data lake)which is not in scope for external analytics vendors.供应商为外部分析提供的解决方案大多以域为中心，而内部供应商为外部分析提供的解决方案大多以域为中心，而内部BIDABIDA架构将架构将支持跨域支持跨域/跨公司分析。跨公司分析。Vendor-provided solutions for external analyt
30、ics are mostly domain-centric while the internal BIDA architecture will enable cross-domain/cross operating company analysis.数据湖的设计是可扩展的，允许存储将来的数据和目前在数据湖的设计是可扩展的，允许存储将来的数据和目前在BIDABIDA范围内的范围内的5 5个目标域中未识别的新用例。个目标域中未识别的新用例。Data Lake design is extensible allowing for future data stores and use cases not
31、 currently identified in the 5 target domains in scope for BIDA.Copyright 2018,Oracle and/or its affiliates.All rights reserved.|Copyright 2018,Oracle and/or its affiliates.All rights reserved.|Copyright 2018,Oracle and/or its affiliates.All rights reserved.|智能机器人客户智能机器人客户 Intelligent Bots Customers
32、17消费者能源机器人消费者能源机器人CONSUMER UTILITY BOT 帐户管理 Account Management 停机 Outages 帐单和付款 Billing&Payment 促销 Promotions会员零售机器人会员零售机器人MEMBER RETAIL BOT 帐户管理 Account Management 调度 Scheduling 接种疫苗 Vaccinations 商店信息 Store Information飞机维修机器人飞机维修机器人AIRCRAFT MAINT.BOT 状态 Status 报告 Reports 资源 Resources 部件 Parts乘客旅行机器
33、人乘客旅行机器人PASSENGER TRAVEL BOT 查找和预订服务 Find&Book packages 门票 Tickets 常问问题回答 FAQ 提醒 Reminders 银行交易 Banking Transactions 客户服务（FAQ）Customer Service(FAQ)国外旅行（ATM）Foreign Travel(ATM)信用卡申请 Credit Card Applications消费者银行机器人消费者银行机器人CONSUMER BANKING BOT保险机器人保险机器人INSURANCE BOT 帐户管理 Account Management 报价 Quotes 索
34、赔 Claims 付款 Payment消费者银行机器人消费者银行机器人CONSUMER BANKING BOT 银行交易 Banking Transactions 客户服务（FAQ）Customer Service(FAQ)消费者安全机器人消费者安全机器人CONSUMER SAFETY BOT 事件管理 Incident Management 状态(Status)通知(Notifications)消费者零售机器人消费者零售机器人CONSUMER RETAIL BOT 反馈和查询 Feedback and inquiries 安装需求 Installation requirements 产品修理
35、 Product repair 账户管理 Account Mgmt.员工员工HCM机器人机器人EMPLOYEE HCM BOT 时间卡(Time Cards)PTO 选择(Pick)学生银行机器人学生银行机器人STUDENT BANKING BOT 银行交易 Banking Transactions 客户服务（FAQ）Customer Service(FAQ)Copyright 2018,Oracle and/or its affiliates.All rights reserved.|Copyright 2018,Oracle and/or its affiliates.All rights
36、 reserved.|Copyright 2018,Oracle and/or its affiliates.All rights reserved.|物联网应用场景 IoT Use Cases18 实时过滤和处理阀门事件 Real-time filtering and processing of valve events 主动部件更换 Proactive parts replacement 与CRM和服务系统集成 Integration with CRM and Service Ticketing system 物联网以提供移动性作为服务 IOT to to deliver mobility
37、 as a service 监控车辆位置以进行计费和地理围栏 Monitoring vehicle location for billing and geo-fencing 于2016年3月在日本推出 Launched in Mar 2016 in Japan 新一代传感器驱动的智能楼宇 Next generation sensor-driven building automation 减少“废物挤压”的数量 Reduce the number of“truck rolls”与Oracle Service Cloud和SAP集成 Integration with Oracle Service
38、Cloud and SAP 更好地推动每个经销商的客户体验 Drive better Customer experience at every dealership 根据驾驶行为提供有针对性的促销活动 Deliver targeted promotions based on driving behavior OBDII与物联网，移动和服务云集成 OBDII integration with IOT,Mobile and Service CloudCopyright 2016,Oracle and/or its affiliates.All rights reserved.|Connecting
39、 people and businesses to information 19将信息 与人和业务 链接链接在一起Copyright 2017,Oracle and/or its affiliates.All rights reserved.|组织组织Organize实验实验Experiment操作操作Operationalize处理处理Process治理治理Govern存储存储Store管理管理Manage机器学习机器学习Machine Learning图数据图数据 Graph空间数据空间数据 Spatial公共数据公共数据Public流数据流数据Streaming企业数据企业数据Enter
40、prise20基本图基本图 Base Diagram用于大数据的甲骨文云平台用于大数据的甲骨文云平台Oracle Cloud Platform for Big data数据服务数据服务Data Services业务分析业务分析Business Analytics企业应用企业应用Enterprise Apps准备准备Prepare分析分析Analyze数据供应者数据供应者Data Providers数据消费者数据消费者Data Consumers数据数据基础架构基础架构Data Infrastructure甲骨文甲骨文AI平台平台 Oracle AI PlatformAI嵌入在嵌入在SaaS和和
41、PaaS中中(Embedded AI in SaaS&PaaS)预测结果，异常的自适应应用程序 Adaptive apps that predict outcomes,anomalies 通过AI自动化的智能平台 Intelligent platform with AI-enabled automation大规模开发平台大规模开发平台(Extensive Development Platform)常见的AI库，ML框架和开发工具 Common AI libraries,ML frameworks,and dev tools高性能基础设施高性能基础设施(High Performance Infr
42、astructure)同类最佳的计算实例，网络和存储 Best in class compute instances,networks,storage专为最终用户和数据科学家而打造Built for end users and data scientists数据准备Data Preparation数据丰富化Data Enrichment数据湖Data Lake机器学习Machine LearningAI算法AI Algorithms深度学习Deep LearningGPU闪存存储Flash Storage25千兆以太网25 GigEthernet数据管理和集成数据管理和集成 Data Mana
43、gement&IntegrationAI开发平台开发平台 AI Development Platform高性能基础设施高性能基础设施 High Performance Infrastructure应用Applications受训模型Trained Models数据DataAI嵌入在嵌入在SaaS和和PaaS中中 AI Embedded in SaaS&PaaS企业企业大数据实验室大数据实验室如何成功？如何成功？How companies succeed with Data Lab?Confidential数据实验室概念架构23Conceptual Data Lab Architecture可操
44、作的事件可操作的事件Actionable Events流处理引擎流处理引擎Streaming Engine数据湖数据湖Data Lake企业数据企业数据&报表报表Enterprise Data&Reporting数据实验室数据实验室Data Lab可操作的指标可操作的指标Actionable Metrics可操作的数据集可操作的数据集Actionable Data Sets事件输入事件输入Input Events执行执行Execution创新创新Innovation探索输出探索输出Discovery Output数据数据DataStructuredEnterprise Data结构化结构化企业
45、数据企业数据培育大数据的世界24Culture Big Data World ABN AMRO Verzekeringen 11 Culture Big data world Analytics Defining hypothesis Collecting data Exploring data Checking hypothesis How does that work?Cooperation is inevitable IT needs help from business Business needs help from IT Outliers,interesting of qualit
46、y issue?New,unexpected insights Distance is impossible Challenging each other “Open”questions Practical approach Virtual Data Team Use the wisdom of the crowd 分析分析假设定义采集数据探索数据检查假设如何运作如何运作合作必不可少IT需要业务的帮助业务需要IT的帮助异常值，有趣的质量问题新的，意外的洞察不能相互疏远不能相互疏远挑战对方开放式问题 实际的做法实际的做法虚拟数据团队集体的力量 ABN AMRO Verzekeringen 11
47、Culture Big data world Analytics Defining hypothesis Collecting data Exploring data Checking hypothesis How does that work?Cooperation is inevitable IT needs help from business Business needs help from IT Outliers,interesting of quality issue?New,unexpected insights Distance is impossible Challengin
48、g each other “Open”questions Practical approach Virtual Data Team Use the wisdom of the crowd 核心团队 业务分析师业务分析师(Business Analyst)项目全生命周期都存在visiting member for duration of project 数据工程师数据工程师(Data Engineer)数据科学家数据科学家(Data Scientist)合规官员共享资源合规官员共享资源(Compliance Officer shared resource)25Core Team业务分析员业务分析
49、员Business Analyst数据科数据科学家学家 Data Scientist合规官员合规官员 Compliance Officer数据工数据工程师程师 Data Engineer总结总结 Summary26勇敢尝试，一定有回报勇敢尝试，一定有回报从小开始，志向远大从小开始，志向远大创建数据实验室创建数据实验室业务和业务和IT是合作伙伴是合作伙伴不要担心失败不要担心失败享受享受 Take the risk,the rewards will come Start small Dream Big Create a Data Lab Partnership between Business&I
50、T Dont be afraid to fail EnjoyCopyright 2017,Oracle and/or its affiliates.All rights reserved.|Confidential Oracle Internal/Restricted/Highly Restricted27 亚太地区第亚太地区第11届全球领导者大会届全球领导者大会11th Global Leaders Conference in APAC 主题：自治数据仓库和大数据主题：自治数据仓库和大数据theme:Autonomous DW and Big Data 客户介绍来自：客户介绍来自：custo
