数字化企业转型大数据解决方案(1).pptx

单击此处编辑母版标题样式,单击此处编辑母版文本样式,二级,三级,四级,五级,www.transwarp.io,Slide Title Goes Here,Body Text,Second level,Third level,Fourth level,Fifth level,2010 Cisco and/or its affiliates.All rights reserved.,Cisco Confidential,Slide Title Goes Here,Body Text,Second level,Third level,Fourth level,Fifth level,2010 Cisco and/or its affiliates.All rights reserved.,Cisco Confidential,Presentation ID,Slide Title,Click to edit Master text styles,Second level,Third level,Fourth level,2016 Cisco and/or its affiliates.All rights reserved.Cisco Public,Slide Title Goes Here,Body Text,Second level,Third level,Fourth level,Fifth level,2010 Cisco and/or its affiliates.All rights reserved.,Cisco Confidential,单击此处编辑母版标题样式,单击此处编辑母版文本样式,二级,三级,四级,五级,www.transwarp.io,Slide Title Goes Here,Body Text,Second level,Third level,Fourth level,Fifth level,2010 Cisco and/or its affiliates.All rights reserved.,Cisco Confidential,Presentation ID,Slide Title,Click to edit Master text styles,Second level,Third level,Fourth level,2016 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Confidential,单击此处编辑母版标题样式,单击此处编辑母版文本样式,二级,三级,四级,五级,数字化企业转型,大数据解决方案,2,变革时代的奏鸣,大数据技术简介,强大的软件功能,坚实的物理基础,新世界的问与答,议程,Presentation ID,跨界颠覆无处不在,汽车制造,公共交通,控制自动化,出租车,快递,航空,酒店,停车场,金融保险,能源,商场,媒体娱乐,房产,安全部门,医疗,教育,Gartner,：,2017,年,十,大战略技术趋势,数字化转型有很多环节需要演进,移动网络,数据无处不在,生产设备,前端应用,供应链,终端设备,安全,大数据,IoT,云,移动设备,100%,of business networks have traffic to malware sites,84%,believe big data delivers high business value,65%,of CEOs consider IoT to be strategic,57%,of organizations will use cloud solutions,81%,of CEOs believe mobility is strategic,行业的快速变更,Inclusive Decision-making,Augmented Decision-making,Situational Awareness,Behavioral Awareness,Dynamic Processes,Dynamic Resources,Hyper-awareness,InformedDecision-Making,Digital,Business,Agility,FastExecution,动态化资源,:,The ability to acquire,deploy,manage,and re-allocate resources(e.g.,talent,technology)as business conditions dictate,形势环境感知,:,The ability to identify changes in an organizations internal and external environments,and to understand which changes matter,行为习惯感知,:,The ability to understand how workers and customers act,what they think,and what they value,动态化流程,:,The ability to rapidly introduce new business processes and adapt existing business processes to changing business conditions,包容化辅助决策,:,The ability to make decisions based on the shared intelligence that emerges from the collaboration of disparate individuals and teams,数据分析辅助决策,:,The ability to incorporate data and analytics into the decision-making processes across an organization,数字化企业业务模型的三个流程环节,数字化之支柱,Applications,500,billion,New generation of applications and services,API,Economy,Online sales to cross$500 billion in,2020,“Big”Data,90%,90%of,the data created in the last two,years.,40,zettabytes by 2020,7,billion,7 billion people will have access to internet by 2020,People,Things,50 billion devices,connected to the internet by 2020.,50,billion,大数据应用场景,10,Media/Entertainment,Viewers/advertising effectiveness,Communications,Location-based advertising,Education&Research,Experiment sensor analysis,Consumer Packaged Goods,Sentiment analysis of what,s hot,problems,Health Care,Patient sensors,monitoring,EHRs,Quality of care,Life Sciences,Clinical trials,Genomics,High Technology/Industrial Mfg.,Mfg quality,Warranty analysis,Oil&Gas,Drilling exploration sensor analysis,FinancialServices,Risk&portfolio analysis,New products,Automotive,Product launch,Dynamic value chain,Monitoring,Retail,Consumer sentiment,Optimized marketing,Law Enforcement&Defense,Threat analysis-social media monitoring,photo analysis,Travel&Transportation,Sensor analysis for optimal traffic flows,Customer sentiment,Utilities,Smart Meter analysis for network capacity,On-line Services/Social Media,People&career matching,Web-site,optimization,算法？建模？我们唯一缺乏的是想象力,来自客户的,诉求,11,传统制造业,设立新的战略数据部,高等教育,开设大数据专业,能源行业,构建智慧运维系统,政府交通,建立智能交通分析系统,物联网，工业,4.0,产生什么？接下来呢？,Industry Landscape is Changing,各个行业,的现状和痛点,实体零售收到电商的巨大冲击，亟需转型和谋求更高效的经营手段，大数据分析是方向之一,实体零售也在开始做自营电商，现在电商和零售的界限也越来越模糊,品牌在大型电商上赚钱的不多，买流量太贵，所以有部分倾向于自己建立渠道,全渠道营销,是所有零售商都在考虑的事情，甚至早下重金，例如百联集团和家化集团,实体零售的数据量偏少，有些甚至为零，如何获得数据是头等大事，特别是外部数据,零售和电商都需要商品,销售预测,、,选品规划、营销触发,的功能,工业,4.0,刚刚起步，应用模式还在摸索中，核心是,CPS(Cyber-physics systems),需要有强大的大数据平台为将来大数据处理的场景做准备,需要有好的,算法模型,做数据挖掘,大型电商都有自主的大数据研发团队，靠自己的力量建立大数据平台,同零售业类似，电商也需要,销售预测,和,选品规划,的功能模块,如何有效地对用户进行精准营销,如何获得外部数据资源以获得更加精准,的用户画像,需要,更多的流量,零售业,制造业,电商,建立在大数据之上的模块,市场方面的应用,ERP,方面的应用,工业方面的应用,管理模块的切换,智能营销,客户分析,追踪的影响,商业洞察,全渠道营销,进销存管理,生产管理,商业智能,物流管控,电子商务,订单,/,商品预测,用户需求,订单信息,产品开发,工艺规划,生产制造,订单,/,商品预测,市场营销领域大数据举例,第三阶段：,应用,第二阶段：,数据管理,&,客户分析,第一阶段：,数据收集,&,整合,实时感知,DSP,Business,Intelligence,模块,消费者洞察,市场细分,跨平台分析,消费者画像,跨媒体跟踪分析,Online,和,offline,数据收集,传播统一的数据存储管理,DMP,平台,DMP,DMP,全渠道营销,百联集团,上海家化,变革时代的奏鸣,大数据技术简介,强大的软件功能,坚实的物理基础,新世界的问与答,议程,Presentation ID,大数据的定义,大数据不仅仅是指数据本身，还包括一系列用来收集、管理、挖掘、分析海量信息并解决复杂问题的技术：,According to IDC“Big data refers not only to data itself but also to a set of technologies designed to collect,manage,mine,andanalyze large collections of information to solve complex problems.”,IDC,At a recent Big Data and High Performance Computing Summit in Boston hosted by Amazon Web Services(AWS),data scientist John Rauser mentioned a simple definition:,任何大到一台计算机处理不过来的数据就是大数据,，,Any amount of data thats too big to be handled by one computer.Some says thats too simplistic.Others say its spot on.,Amazon Web Services(AWS),“Big data”,是指数据集合的尺寸超过典型数据库软件工具的捕捉、存储、管理和分析能力。,refers to datasets whose size is beyond the ability of typical database software tools to capture,store,manage,and analyze.,MGI also says and proves strong evidence that big data can play a significant economic role to the benefit not only of private commerce but also of national economies and their citizens.Data can create significant value for the world economy,enhancing the productivity and competitiveness of companies and the public sector and creating substantial economic surplus for consumers.,McKinsey Global Institute,Foundation Research and Analytics Team,我们所面对的世界,非结构化数据,90%,，,2020,40 ZB,Source:,IDC,Digital Universe Study,我们所面对的世界,非结构化数据,90%,，,2020,40 ZB,多结构化数据,Variety,:,文字,/,图片,/,视频,/,文档,Petabytes,海量信息,Volume:,传统存储,/,计算无法处理,速度,VELOCITY:,快速及时有效的分析,+,ORGANIZE+ANALYZE,价值,VALUE,:,单条信息并无太大价值，但庞大的数据量蕴含巨大财富,Acquire/,Access,Process,Decide,大数据的四大特征,4,个”,V,”,Hadoop,是一个分布式存储和分析数据的容错框架。它由两个主要组件构成：,Hadoop,文件系统（,HDFS,）,数据存储于,多个硬件,中,，其中,一个,出故障的概率是非常高的。避免数据丢失的常见做法是复制,，,通过系统保存数据的冗余副本，在故障发生时，可以使用数据的另一份副本。这就是冗余磁盘阵列的工作方式。Hadoop的文件系统HDFS(Hadoop Distributed Filesystem)就是,这样工作的。,MapReduce,应用引擎,大,部分分析任务需要通过某种方式把数据合并起来，即从一个磁盘读取的数据可能需要和,其它多个,磁盘中读取的数据合并起来才能使用。MapReduce提供了一个编程模型，其抽象出上述磁盘读写的,数据,，将其转换为计算一个由成对键值组成的数据集。,什么是,Hadoop,？解决的问题,Hadoop,的主要组件,Hadoop has many building blocksAt the base is a way to Store and Process unstructured data,Hadoop Distributed File System,(HDFS),At the base is a Self-healing clustered storage system.,Map-Reduce,Distributed Data Processing,PIG,Hive,Sqoop,Top level abstractions,Top level Interfaces,ETL Tools,BI Reporting,RDBMS,HBASE,Database with Real-time access,Apps API,21,Flume,五大功能,Big Data,PC,POS,Smart,Phone,Cellular,phone,GPS,IC,tag,Smart mater,Sensor,SNS,AV,数据源,用自动算法代替支持人工决策：,复杂的数据分析可以大大优化决策流程、降低风险、挖掘潜在价值,新业务模式的创新,:,产品、服务,客户群分类和精细化服务：,通过产品、服务的裁剪，为不同客户群提供更为精细的服务,增加透明度：,所有应用和客户都可以在第一时间内访问到需要的数据，可以产生巨大价值,大数据的价值优势,.,大数据的价值优势,美国医疗服务业：,每年价值,3000,亿美元,大约,0.7%,的年生产率增长,制造业：,产品开发、组装成本降低,50%,运营资本降低,7,全球个人位置数据：,服务提供商收入,1000,亿美元,或最终用户价值达,7000,亿美元,美国零售业：,可能的净利润增长水平,60%,或,0.51%,的年生产率增长,Data Source:McKinsey Global Institute,Big data:The next frontier for innovation,competition,and productivity,Foundation Research and Analytics Team,Big Data,Financial Services,Fidelity National Information Services(FIS),利用大数据监测信用卡欺诈,他们销售基于,ParAccel,大数据的信用卡风险管理和诈骗监测系统,作为信用卡诈骗的新的方法，信用卡运行系统可以根据这一系统实时接受或拒绝信用卡交易,According to ParAccel:“With PADB,FIS can engage in two-way conversations with its data to optimize detection for its customers,while minimizing impact on legitimate clients.”,大数据在金融服务行业的优势,Foundation Research and Analytics Team,金融风险管理,满足银监会、巴塞尔协议的风险管理要求,及时有效的交易风险分析,消费行为分析、实时促销和积分管,理,交易的实时监控,金融产品创新,提升客户体验,25,变革时代的奏鸣,大数据技术简介,强大的软件功能,坚实的物理基础,新世界的问与答,议程,Presentation ID,大数据时代的企业数据库架构,EDW,Operational,(Transactional),ETL,EDW,BI/Reports,Traditional,New,Web,Machine,ETL,Big Data(Hadoop,NoSQL),Operational,(Transactional),ETL,BI/Reports,Dashboards,Operational,(Transactional),Operational,(Transactional),星环信息科技公司介绍,中国,最久,Hadoop,核心开发团队,研发，支持和销售团队来自于,Intel,Google,IBM,，,Oracle,等跨国企业,2016,年,1,季度完成,1.55,亿,B,轮,融资,No.1,中国落地案例最多,国内最多的落地应用案例,2014,年进入中央政府采购网,国内技术最,领先,大数据,/,数据库基础,软件,超越,硅谷的企业级架构及功能模块,大数据平台市场占有率最高,唯一进入,Gartner,魔力象限中国公司,支持,复杂关键应用的大数据,平台,高度兼容,OLAP,oracle,应用,和高并发,OLTP,查询,300%,年营业额和客户增长,星环科技被,Gartner,定位为,全球最具发展前景的新型大数据厂商,近日，国际知名咨询机构Gartner针对当前数据仓库及数据管理解决方案市场，在其魔力象限1.中对全球21家厂商进行了对比分析，其中，Oracle、Teradata、Oracle和Microsoft三家公司包揽了前三甲，,而,在,大数据核心技术最领先的,公司,却是来自中国的公司,星环科技（Transwarp），这也是,该领域的魔力象限中第一次出现中国公司。,Strengths,Although a young vendor,Transwarp has gained traction in the Chinese market.It has won 200 clients in less than 18 months.,Transwarp has a unique set of capabilities,such as its Inceptor SQL component based on,Apache Spark,with Oracle SQL and PL/SQL compatibility supporting create,read,update,delete(CRUD)and ACID operations.This component is particularly praised by reference,customers.,Reference customers indicated that they are very satisfied with Transwarps product,as well as,with the support and training that the company offers.,优势,星环科技虽然年轻，但是已经在中国市场中颇具影响力星环科技在18个月内赢取了200个客户。,星环科技的产品有其独特的功能，例如它的SQL引擎Inceptor，基于Apache Spark，兼容Oracle SQL和PL/SQL，支持事务处理的CRUD(CREATE,READ,UPDATE,DELETE)并能保证ACID。Inceptor在被调查的用户中受到了非常高的评价。,被调查的用户表示他们对星环的产品、支持以及提供的培训都非常满意。,Cautions,So far,Transwarp operates in China only.That said,the size of the Chinese market,and its,specific requirements,offers plenty of scope for Transwarp to expand.,Transwarp has yet to offer a cloud solution,although it indicates that the cloud is on its roadmap.,Reference customers pointed to some missing functionality,particularly with regard to administration and management,and highlighted a lack of skills in the market.However,across,the whole spectrum of customer experience,Transwarps customers awarded scores equal to,the average for this market.,注意,目前，星环仅在中国有业务。虽然如此，中国庞大的市场以及中国市场特有的要求给星环的发展空间巨大。,虽然暂时还没有推出云上的解决方案，但是星环科技的云解决方案已经在计划中。,被调查的客户指出星环的产品还有一些功能的缺失，尤其在产品的管理功能方面。被调客户还指出市场中对口人才的稀缺。即使如此，被调客户对星环科技各方面的评价都持平报告中的平均水平。,优势,l,星环科技虽然年轻，但是已经在中国市场中颇具影响力,星环科技在,18,个月内赢取了,200,个客户。,l,星环科技的产品有其独特的功能，例如它的,SQL,引擎,Inceptor,，基于,Apache Spark,，兼容,Oracle SQL,和,PL/SQL,，支持事务处理的,CRUD(CREATE,READ,UPDATE,DELETE),并能保证,ACID,。,Inceptor,在被调查的用户中受到了非常高的评价。,l,被调查的用户表示他们对星环的产品、支持以及提供的培训都非常满意。,注意,l,目前，星环仅在中国有业务。虽然如此，中国庞大的市场以及中国市场特有的要求给星环的发展空间巨大。,l,虽然暂时还没有推出云上的解决方案，但是星环科技的云解决方案已经在计划中。,l,被调查的客户指出星环的产品还有一些功能的缺失，尤其在产品的管理功能方面。被调客户还指出市场中对口人才的稀缺。即使如此，被调客户对星环科技各方面的评价都持平报告中的平均水平。,星环科技,公安交通,山东省公安厅交管局,福建省,公安厅交管局,安徽,省公安厅交管局,吉林,省公安厅交管局,陕西,省公安厅交管局,广东省公安厅,四川省公安厅,中国民航,浙江省台州市公安局,浙江省义乌市交警,浙江省湖州市交警,。,金融行业,中国平安银行,中国民生银行,山东恒丰银行,四川农信社,BEA,东亚银行,包商银行,浙江农信社,江苏银行,中国银行,交通银行,中国人寿,中泰证券,中国邮政储蓄银行,山东城商行。,NO1,运营商,广东省中国移动,湖北省中国移动,广西省中国移动,江苏省中国电信,爱立信：深圳，河南移动,黑龙江,，江苏，香港,移动,上海移动,中国联通,联通研究院,珠海移动,。,政府能源,中国工商总局,安徽省地方税务局,北京市政府道路安全中心,宁波经信委,中国电子科技集团研究所,中国电力科学院南京分院,南网广州供电局,南网佛山供电局,江苏电科院,燕山石化,宝钢集团,。,其他行业,广电华数传媒,华通云数据科技,锦江电商,中国邮政速递物流,EMS,重庆邮电大学,西北大学,青海大学,山东科技大学,。,成功案例,200+,成功案例,200+,成功案例,200+,成功案例,200+,星环科技典型,案例,(,落地案例最多）,我们的部分客户,200,个,Positions,of,Transwarp,Products,Analytics as a Service,Analytics Service&,Applications,Transformation,Discovery&,Visualization Tools,Machine Learning&,Statistics Tools,Hadoop Distributions,&Analytical Databases,Infrastructure,Transwarp Data Hub,架构图,最完整的,SQL,支持,99%,的,SQL,2003,支持，,唯一,支持,PL/SQL,的引擎（,98%,），,唯一,支持,ACID,分布式事务的,SQL,引擎；定位数据仓库和数据集市市场，可用于补充或替代,Oracle,、,DB2,等分析用数据库。,高效内存,/SSD,计算,第一个,支持,SSD,的基于,Hadoop,的高效计算引擎，可比硬盘快一个数量级；可用于建立各种数据集市，对接多种主流报表工具。,最完整的分布式机器学习算法库,支持,最全,（超过,50,余种）的分布式统计算法和机器学习算法，同时整合超过,5000,个,R,语言算法包。适合金融业风险控制、反欺诈、文本分析、精准营销等应用。,支持最完整,SQL,和索引的,NoSQL,数据库,支持,SQL2003,、索引、全文索引，支持图数据库和图算法，支持非结构化数据存储,支持高并发查询,最健壮和功能丰富的流处理框架,支持真正的,Exactly,Once,语义,支持所有组件的高可用,(HA),支持流式,SQL,和流式机器学习,Transwarp Proprietary,Apache Projects,Transwarp Manager,资源管理,YARN,(,内置,Transwarp Extension),优化存储,HDFS,(,内置,Transwarp Erasure Code),批处理框架,MapReduce2,协作服务,Zookeeper,全文搜索,Optimized Elastic Search,Discover,数据挖掘,机器学习,Inceptor,PL/SQL,引擎,交互,分析,、图计算,Stream,流处理引擎,Hyperbase,NoSQL,数据库,综合搜索,Guardian,安全管控,实时同步,Data Alive,消息队列,Kafka,日志采集,Flume,数据集成,Sqoop,数据集成,Data Integration,SQL,开发辅助,Waterdrop,可视化挖掘,Midas,交互工具,HUE,交互分析,Zeppelin,工作流,Oozie,内置交互工具,Build-in Interactive,Tools,Advantages of TDH,1.Complete SQL Support,2.Superier Performance,3.ACID/Transaction Support,4.Distributed Stream,SQL,5.Rich ML Algorithm Library,6.Unified Security,Use SQL to create streams,and run ANSI SQL and PL/SQL stored procedures over streaming events.,Unified batch and event driven processing on the same engine.,HA,low latency,flow control,Distributed Transactions,Batch/Incremental CRUD Operations,MVCC,&Two Phase Locking to guarantee consistency,Best performance for 1TB/10TB/100TB TPC-DS benchmark tests,。,In-memory/On-SSD columnar store for low latency interactive analysis,ANSI,SQL 2003,（,99%,）,Oracle PL/SQL,（,98%,）,DB2 SQL/PL,（,90%,）,Teradata SQL,（,90%,）,Easy to migrate legacy applications or develop new,apps,SQL to setup security rules for all components.,Single Sign On,Role based Access Control,Row/column granularity access control.,70 distributed statistics and machine learning algorithms,Seamless R integration to call distributed algorithms.,Connectors for Rapdminers for ML pipeline creation/modeling.,Fusion Distributed Execution Engine,分布式执行引擎,Association,Mining,关联,/,推荐,Classification,分类算法,Clustering,聚类算法,Sequential,Analysis,时序分析,Regression,回归算法,Deep,Learning,深度机器学习,Dimension,Reduction,主成分分析,Statistics,统计算法,R,Runtime,Library,R,语言动态运行库,Belief Network,信念网络,Graph,图计算,Sampling,采样算法,Discriminate,Analysis,判别分析,Reinforcement,增,强学习,Decision Methods,决策方法,Factor Analysis,因子分析,Genetic,遗传算法,Java/Scala Interfaces,Rapidminer Graphical IDE,Rstudio IDE,Hubble Core,算法计算接口,Graph engine,图计算引擎,Customized Plugins,自定义插件,Transwarp Connector,SQL Interfaces to connect data sources,Industry Templates,行业模板,Feature Eng,特征工程