微軟汽車行業(yè)大數(shù)據(jù)平臺(tái)建設(shè)探討

1、MICROSOFT CONFIDENTIAL汽車行業(yè)汽車行業(yè) - - 數(shù)據(jù)驅(qū)動(dòng)的時(shí)代數(shù)據(jù)驅(qū)動(dòng)的時(shí)代MICROSOFT CONFIDENTIAL汽車行業(yè)面臨的挑戰(zhàn)The Connected Marketing, Sales & ServiceOthersThe Connected VehicleConnected Product InnovationConnected OperationsTransformation OpportunitiesCustomer ExamplesMICROSOFT CONFIDENTIAL信息化的縱深發(fā)展，帶來汽車行業(yè)的大變革數(shù)字化轉(zhuǎn)型 60%的客戶的交互都是通過

2、數(shù)字渠道和經(jīng)銷商網(wǎng)絡(luò) 車企需要增強(qiáng)他們的價(jià)值網(wǎng)絡(luò)，通過數(shù)字渠道的方式來洞察客戶全生命周期的管理。車輛信息Hub的轉(zhuǎn)型 智能互聯(lián)車輛 到2020你那互聯(lián)車輛的滲透率將從20%上升到90% 開放的生態(tài)環(huán)境將給車企帶來更多的挑戰(zhàn)，也給車企提供更多的服務(wù)機(jī)會(huì) 獨(dú)特的互聯(lián)客戶體驗(yàn)是未來的主要方向高度互聯(lián)的業(yè)務(wù)變化要求無處不在的客戶體驗(yàn)需要3MICROSOFT CONFIDENTIAL汽車行業(yè)信息化的趨勢(shì)為四個(gè)“Connected”今天的技術(shù)趨勢(shì)正在引爆機(jī)會(huì)！移動(dòng)企業(yè)社交大數(shù)據(jù)云計(jì)算物聯(lián)網(wǎng)Connected Marketing, Sales & Service客戶更愿意通過數(shù)字渠道結(jié)合經(jīng)銷商網(wǎng)絡(luò)來做決定C

3、onnected Operations成本和風(fēng)險(xiǎn)管理依然是企業(yè)制造和運(yùn)營的關(guān)鍵因素Connected Product Innovation智能互聯(lián)的產(chǎn)品驅(qū)動(dòng)了開發(fā)過程中的創(chuàng)新Connected Vehicle驅(qū)動(dòng)更多的個(gè)性化客戶體驗(yàn)和持續(xù)服務(wù)4MICROSOFT CONFIDENTIAL531531 應(yīng)用46004600 接口 34003400 晚間批量任務(wù)沒有沒有 “端到端” 的流程的流程. 海量非結(jié)構(gòu)化數(shù)據(jù)支持效率: 一般一個(gè)一般一個(gè)員員工只能支工只能支持持1717個(gè)個(gè)應(yīng)應(yīng)用用車企的“Connected”首先意味著大量業(yè)務(wù)數(shù)據(jù)的整合MICROSOFT CONFIDENTIAL6所有的數(shù)據(jù)都

4、是復(fù)雜、耗時(shí)和難以獲取數(shù)量 數(shù)據(jù)爆炸性增長集成 各自為政的數(shù)據(jù)孤島質(zhì)量 數(shù)據(jù)質(zhì)量不可靠行動(dòng) 難以快速獲得數(shù)據(jù)價(jià)值然而：業(yè)務(wù)整合只是一個(gè)過程MICROSOFT CONFIDENTIAL2. 復(fù)雜的數(shù)據(jù)流和監(jiān)控規(guī)則復(fù)雜的數(shù)據(jù)流和監(jiān)控規(guī)則7.機(jī)器自學(xué)習(xí)機(jī)器自學(xué)習(xí)1. 可擴(kuò)展的數(shù)據(jù)鏈接和數(shù)據(jù)獲取可擴(kuò)展的數(shù)據(jù)鏈接和數(shù)據(jù)獲取3. 可按地域的云存儲(chǔ)可按地域的云存儲(chǔ)4. 大數(shù)據(jù)大數(shù)據(jù)5. BI商業(yè)智能商業(yè)智能5. BI商業(yè)智能商業(yè)智能5. BI商業(yè)智能商業(yè)智能6. 客戶和服務(wù)管理客戶和服務(wù)管理6. 客戶和服務(wù)管理客戶和服務(wù)管理車企需要構(gòu)建這樣的大數(shù)據(jù)平臺(tái)和業(yè)務(wù)互聯(lián)MICROSOFT CONFIDENTIAL8

5、互聯(lián)大數(shù)據(jù)平臺(tái)帶來的價(jià)值客戶親密度情景體驗(yàn) | 跨設(shè)備體驗(yàn)關(guān)系生命周期管理crm | plm | scm | dms機(jī)器自學(xué)習(xí)預(yù)測(cè) | 分析云平臺(tái) + 基礎(chǔ)架構(gòu)全局化 | 可擴(kuò)展DataMICROSOFT CONFIDENTIAL汽車行業(yè)互聯(lián)的大數(shù)據(jù)平臺(tái)方案The Connected Marketing, Sales & ServiceOthersThe Connected VehicleConnected Product InnovationConnected OperationsTransformation OpportunitiesCustomer ExamplesMICROSOFT C

6、ONFIDENTIALHadoop 集群采集和預(yù)處理車聯(lián)網(wǎng)Connected carAPPsLOBCRMSAPEDW 數(shù)據(jù)倉庫Streaming實(shí)時(shí)分析互聯(lián)網(wǎng)Internet官方網(wǎng)站社區(qū)輿論情報(bào)車聯(lián)網(wǎng)RFID車載娛樂終端試驗(yàn)車日志處理企業(yè)大數(shù)據(jù)中心數(shù)據(jù)利用ETL分析、展現(xiàn)和其他應(yīng)用Connector算法和模型R Server /機(jī)器學(xué)習(xí)/分析挖掘檢測(cè)監(jiān)控預(yù)測(cè)維護(hù)分析展現(xiàn)市場(chǎng)營銷大數(shù)據(jù)中心平臺(tái)整體架構(gòu)MICROSOFT CONFIDENTIALLanding LayerBatch LayerServing LayerSpeed LayerRaw Data StorageStatic Views

7、PrecomputingPrecomputingAd-hoc Batch ViewsStatic Batch Views實(shí)時(shí)數(shù)據(jù)流Raw Data Raw Data StorageStoragePre-computingPre-computingBatch ViewsBatch ViewsLegend:Legend:Layer boundaryData flow (with direction indicated)Data exchangeData LandingData Landing數(shù)據(jù)采集數(shù)據(jù)處理數(shù)據(jù)展現(xiàn)Indexing and ViewsReal-Time Processing, Ag

8、gregationsStreamingStreaming實(shí)時(shí)數(shù)據(jù)流實(shí)時(shí)數(shù)據(jù)流Processing Microsoft R ServerSQL ModelingSQL ModelingData AreaData Area大數(shù)據(jù)中心平臺(tái)邏輯架構(gòu)企業(yè)私有云平臺(tái)基礎(chǔ)架構(gòu)MICROSOFT CONFIDENTIAL大數(shù)據(jù)中心三大組成部分基礎(chǔ)架構(gòu)基礎(chǔ)架構(gòu)-私有云平臺(tái)私有云平臺(tái)數(shù)據(jù)存儲(chǔ)及運(yùn)算數(shù)據(jù)存儲(chǔ)及運(yùn)算-Hadoop平臺(tái)平臺(tái)數(shù)據(jù)分析及展示數(shù)據(jù)分析及展示-R-Server/BI數(shù)據(jù)分析平臺(tái)數(shù)據(jù)分析平臺(tái)123MICROSOFT CONFIDENTIAL虛擬化管理工具服務(wù)器存儲(chǔ)網(wǎng)絡(luò)設(shè)備服務(wù)流程平臺(tái) System

9、 Center Service Manager數(shù)據(jù)中心管理員（資源管理）應(yīng)用管理員（應(yīng)用擴(kuò)容）最終用戶（服務(wù)申請(qǐng)）知識(shí)庫報(bào)表 系統(tǒng)管理數(shù)據(jù)、流程總線配置管理工具監(jiān)控管理工具門戶管理平臺(tái) SharePoint Server災(zāi)備管理工具傳統(tǒng)物理資源虛擬化資源微軟私有云(IaaS)平臺(tái)邏輯架構(gòu)MICROSOFT CONFIDENTIAL構(gòu)建統(tǒng)一管理的私有云平臺(tái)MICROSOFT CONFIDENTIAL私有云的運(yùn)營MICROSOFT CONFIDENTIAL基礎(chǔ)架構(gòu)監(jiān)控MICROSOFT CONFIDENTIAL自動(dòng)化修復(fù)MICROSOFT CONFIDENTIAL動(dòng)態(tài)優(yōu)化資源MICROSOFT C

10、ONFIDENTIAL更新管理MICROSOFT CONFIDENTIAL服務(wù)交互自動(dòng)化MICROSOFT CONFIDENTIAL自動(dòng)化體檢MICROSOFT CONFIDENTIAL記賬/收費(fèi)MICROSOFT CONFIDENTIAL本地災(zāi)備：主站點(diǎn)數(shù)據(jù)中心機(jī)房的冗余MICROSOFT CONFIDENTIAL可備份到公有云應(yīng)用創(chuàng)新應(yīng)用創(chuàng)新混合的超大規(guī)模的企業(yè)級(jí)別的Microsoft AzurePublic, Global, Shared Datacenters私有云數(shù)據(jù)中心 Core Software InfrastructureIaaSPaaSComputeStorageNetwor

11、kAzure Management Portal Cloud-inspired infrastructurePowered by Windows Server, Hyper-V, System Center (future Azure Stack)Windows Azure Pack(future Azure Stack Portal)IaaSPaaSComputeStorageNetworkAzure Global DatacentersDatacenter InfrastructureLinuxWindows ServerLinuxWindows ServerSystem Center +

12、 OMS從私有云擴(kuò)展到混合云MICROSOFT CONFIDENTIAL大數(shù)據(jù)中心三大組成部分基礎(chǔ)架構(gòu)基礎(chǔ)架構(gòu)-私有云平臺(tái)私有云平臺(tái)數(shù)據(jù)存儲(chǔ)及運(yùn)算數(shù)據(jù)存儲(chǔ)及運(yùn)算-Hadoop平臺(tái)平臺(tái)數(shù)據(jù)分析及展示數(shù)據(jù)分析及展示-R-Server/BI數(shù)據(jù)分析平臺(tái)數(shù)據(jù)分析平臺(tái)123MICROSOFT CONFIDENTIAL為什么需要Hadoop數(shù)據(jù)來源數(shù)據(jù)系統(tǒng)數(shù)據(jù)訪問業(yè)務(wù)分析定制應(yīng)用現(xiàn)有數(shù)據(jù)數(shù)據(jù)庫運(yùn)營應(yīng)用新數(shù)據(jù)有限的數(shù)據(jù)不足以管理現(xiàn)有的數(shù)據(jù)，更不用說新數(shù)據(jù)，同時(shí)還要維護(hù)規(guī)模性能。數(shù)據(jù)首先必須是結(jié)構(gòu)化的。有限的洞察有限的訪問和較差的數(shù)據(jù)視角導(dǎo)致較差的分析和低采用度。 很難將洞察轉(zhuǎn)化為行動(dòng)。復(fù)雜的架構(gòu)更多的數(shù)據(jù)，

13、更多的用戶，更多的工具制造了復(fù)雜性。統(tǒng)一安全中的漏洞讓不良行為者可以有訪問權(quán)。傳統(tǒng)方式的設(shè)計(jì)是為結(jié)構(gòu)化：結(jié)構(gòu)化的數(shù)據(jù)結(jié)構(gòu)化的分析結(jié)構(gòu)化的流程MICROSOFT CONFIDENTIAL為什么需要Hadoop1)數(shù)據(jù)類型的限制Enterprise Data Warehouse應(yīng)用數(shù)據(jù)源結(jié)構(gòu)化非結(jié)構(gòu)化加載Staging Environment 傳統(tǒng)架構(gòu)Enterprise Data Warehouse服務(wù)ELT歸檔BI 應(yīng)用建模報(bào)表ETLStorage #1Storage #2Storage NIngest處理加載1MICROSOFT CONFIDENTIAL為什么需要Hadoop1)數(shù)據(jù)類型的限

14、制2) 處理能力的限制Enterprise Data Warehouse應(yīng)用數(shù)據(jù)源結(jié)構(gòu)化非結(jié)構(gòu)化IngestStaging Environment 傳統(tǒng)架構(gòu)Enterprise Data WarehouseServeELTArchiveBI 系統(tǒng)建模報(bào)表ETLStorage #1Storage #2Storage NIngestProcessLoad122MICROSOFT CONFIDENTIAL為什么需要Hadoop1)數(shù)據(jù)類型的限制2) 處理能力的限制3) 數(shù)據(jù)容量的限制Enterprise Data WarehouseApplicationsData SourcesStructured

15、UnstructuredIngestStaging Environment 傳統(tǒng)架構(gòu)Enterprise Data WarehouseServeELTArchiveBI SystemModelingReportingETLStorage #1Storage #2Storage NIngestProcessLoad1223MICROSOFT CONFIDENTIAL新的方式1)接收更多的數(shù)據(jù)ApplicationsData SourcesStructuredUnstructuredStaging Environment Hadoop架構(gòu)Enterprise Data WarehouseEDHIn

16、gestIngestActive Structured DataServeServeELTArchive Load1ETLBI SystemModelingReportingMICROSOFT CONFIDENTIAL新的方式1接收更多的數(shù)據(jù)2)強(qiáng)大的并發(fā)處理能力ApplicationsData SourcesStructuredUnstructuredStaging Environment Hadoop架構(gòu)Enterprise Data WarehouseEDHIngestIngestActive Structured DataServeServeELTArchive Load21ETLBI

17、 SystemModelingReportingMICROSOFT CONFIDENTIAL新的方式1) 接收更多的數(shù)據(jù)2) 強(qiáng)大的并發(fā)處理能力3) 全量數(shù)據(jù)在線ApplicationsData SourcesStructuredUnstructuredStaging Environment Hadoop架構(gòu)Enterprise Data WarehouseEDHIngestIngestActive Structured DataServeServeELTArchive Load231ETLBI SystemModelingReportingMICROSOFT CONFIDENTIALHado

18、op-企業(yè)級(jí)的數(shù)據(jù)HUBHadoop 提供：一個(gè)地方用于無限任何類型的數(shù)據(jù)統(tǒng)一的，多框架的數(shù)據(jù)訪問領(lǐng)先的性能和可擴(kuò)展性企業(yè)要求：高性能開源，開放標(biāo)準(zhǔn)完整的系統(tǒng)和數(shù)據(jù)管理企業(yè)級(jí)的安全性全面數(shù)據(jù)監(jiān)管安全和管理無限存儲(chǔ)處理發(fā)現(xiàn)制模服務(wù)部署靈活性現(xiàn)場(chǎng)設(shè)備過程化系統(tǒng)共有云私有云混合云MICROSOFT CONFIDENTIALHadoop: 擴(kuò)展性 & 靈活性 存儲(chǔ) & 計(jì)算The Hadoop傳統(tǒng)數(shù)據(jù)倉庫$30,000+ per TB昂貴而遙不可及 擴(kuò)展困難 網(wǎng)絡(luò)成為不可避免的瓶頸 只能處理結(jié)構(gòu)化關(guān)系型數(shù)據(jù) 很難增加新的字段和數(shù)據(jù)類型昂貴的、專用的、“可靠的”服務(wù)器昂貴的軟件許可證Network數(shù)據(jù)存

19、儲(chǔ)(SAN, NAS)計(jì)算(RDBMS, EDW)$300-$1,000 per TB經(jīng)濟(jì)且可以企及 可無限平行擴(kuò)展 網(wǎng)絡(luò)不再是瓶頸 輕松攝取任何類型的數(shù)據(jù) 靈活的讀取時(shí)檢查數(shù)據(jù)類型的訪問方式商業(yè)化的“不怎么可靠”的服務(wù)器混合的開源軟件計(jì)算(CPU)內(nèi)存存儲(chǔ)(Disk)zzMICROSOFT CONFIDENTIAL大數(shù)據(jù)中心三大組成部分基礎(chǔ)架構(gòu)基礎(chǔ)架構(gòu)-私有云平臺(tái)私有云平臺(tái)數(shù)據(jù)存儲(chǔ)及運(yùn)算數(shù)據(jù)存儲(chǔ)及運(yùn)算-Hadoop平臺(tái)平臺(tái)數(shù)據(jù)分析及展示數(shù)據(jù)分析及展示-R-Server/BI數(shù)據(jù)分析平臺(tái)數(shù)據(jù)分析平臺(tái)123MICROSOFT CONFIDENTIAL微軟數(shù)據(jù)產(chǎn)品家族RDBMSFlat/Excel

20、 fileXMLApplicationStream DataDataWarehouseSSRSSharePointWeb BrowserDatazen ServiceDatazen AppSSRS forSharepointSocial DataSSASData Mining ResearchMulti-Dimension ModelAPS / PDWSSISSQL ServerTabular ModelExcelPowerPivot ModelPerformance PointAzureService BusEvent HubHDInsightAzure SQL DBMachine Lear

21、ningStream InsightSource of Data / BrowserWeb Application / Excel / O365SQL Server Service ComponentImportant Function / Add-inService on Azure PlatformAPS / PDWStreamAnalysisRevolutionRDocument DBSupport to EmbeddedR ScriptPower BI SaaSSolutionPower BISaaSPower BI SitePowerPivot Add-inPower View Ad

22、d-inPower QueryPower ViewPower MapAzure PortalData FactoryPower BI DesktopAzure SQL DWMICROSOFT CONFIDENTIAL微軟提供從自建數(shù)據(jù)中心到云端的完整解決方案MICROSOFT CONFIDENTIAL Analyst ReportsPeriod Leadership PositionGartner Magic Quadrant For Data Warehouse Database Management System For AnalyticsFeb 2015LeaderGartner Mag

23、ic Quadrant For Business Intelligence And Analytics PlatformsFeb 2015LeaderGartner Magic Quadrant For Operational Database Management SystemOct 2015Leader微軟今天在商務(wù)智能和數(shù)據(jù)倉儲(chǔ)中的領(lǐng)導(dǎo)地位MICROSOFT CONFIDENTIALMicrosoft Azure微軟和HadoopMICROSOFT CONFIDENTIAL語言平臺(tái)#1 Procedural Language optimized for Statistics and Da

24、ta Science A Data Visualization Framework Provided as Open Source社區(qū) 3M+ Statistical Analysis and Machine Learning Users Taught in Most University Statistics Programs Active User Groups Across the World生態(tài)環(huán)境 CRAN: 7500+ Freely Available Algorithms, Test Data and Evaluations Many Applicable to Big Data

25、 If Scaled什么是 R?Tool Use for Data ScienceOReilly Data Science Survey 2014 (max=80%)MICROSOFT CONFIDENTIALStrategic RationaleThe leading providerof advanced analytics software and servicesbased on open source R, since 2007 REVOLUTION R: The enterprise-grade predictive analytics application platform b

26、ased on the R language微軟和Revolution AnalyticsMICROSOFT CONFIDENTIAL基于硬盤的擴(kuò)展性 多線程商業(yè)支持5000個(gè)算法分析包+ RevoScaleR 大數(shù)據(jù)分析包43商業(yè)許可內(nèi)存限制單線程開源社區(qū)支持5000個(gè)算法分析包開源算法執(zhí)行風(fēng)險(xiǎn)大數(shù)據(jù)大數(shù)據(jù)分析速度分析速度企業(yè)級(jí)企業(yè)級(jí)廣度和深度廣度和深度商業(yè)上可行性商業(yè)上可行性43為什么要Revolution AnalyticsR是開源的數(shù)據(jù)分析軟件，并驅(qū)動(dòng)分析創(chuàng)新，但是.對(duì)企業(yè)而言，R有諸多局限性MICROSOFT CONFIDENTIALRevolution R Enterprise 7

27、.4 (RRE)全套大數(shù)據(jù)分析平臺(tái)全套大數(shù)據(jù)分析平臺(tái)R+CRANRevolution R OpenDistributedRDeployRDevelopRScaleRConnectR高性能開源R plusplus:可連接到大數(shù)據(jù)對(duì)象的數(shù)據(jù)源大數(shù)據(jù)高級(jí)分析多平臺(tái)支持 開發(fā)和生產(chǎn)In-Hadoop 和 in-Teradata 預(yù)測(cè)模型為數(shù)據(jù)分析和模型開發(fā)人員設(shè)計(jì)的IDE安全的，可擴(kuò)展的R模型部署技術(shù)支持，培訓(xùn)和專業(yè)服務(wù)44微軟整合Revolution Analytics為Microsoft R-ServerMICROSOFT CONFIDENTIALMicrosoft R Server provid

28、es a unique opportunity to deliver our advanced analytics capabilities to customers who have already invested in storing their data on non Microsoft platforms like Hadoop, Teradata and LinuxMicrosoft R-Server將繼續(xù)對(duì)非微軟平臺(tái)的支持MICROSOFT CONFIDENTIALBest of Both Worlds用用SQL 快速查詢快速查詢 & in-memory ColumnStore

29、indexes用用 R于數(shù)據(jù)探索、于數(shù)據(jù)探索、 預(yù)測(cè)建模、預(yù)測(cè)建模、 Scoring和可視化和可視化使用SQL Server的R Service構(gòu)建企業(yè)智能應(yīng)用Microsoft R-Server作為SQL Server2016內(nèi)置的服務(wù)MICROSOFT CONFIDENTIALData import Delimited, Fixed, SAS, SPSS, OBDCVariable creation & transformationRecode variablesFactor variablesMissing value handlingSort, Merge, SplitAggregat

30、e by category (means, sums)Min / Max, Mean, Median (approx.)Quantiles (approx.)Standard DeviationVarianceCorrelationCovarianceSum of Squares (cross product matrix for set variables)Pairwise Cross tabsRisk Ratio & Odds RatioCross-Tabulation of Data (standard tables & long form)Marginal Summaries of C

31、ross TabulationsChi Square TestKendall Rank CorrelationFishers Exact TestStudents t-TestSubsample (observations & variables)Random Sampling數(shù)據(jù)預(yù)處理統(tǒng)計(jì)檢驗(yàn)抽樣描述性統(tǒng)計(jì)Sum of Squares (cross product matrix for set variables)Multiple Linear RegressionGeneralized Linear Models (GLM) exponential family distributions

32、: binomial, Gaussian, inverse Gaussian, Poisson, Tweedie. Standard link functions: cauchit, identity, log, logit, probit. User defined distributions & link functions.Covariance & Correlation MatricesLogistic RegressionClassification & Regression TreesPredictions/scoring for modelsResiduals for all m

33、odels預(yù)測(cè)模型K-MeansDecision TreesDecision ForestsGradient Boosted Decision TreesNave Bayes聚類分析分類模擬變量選擇Stepwise RegressionSimulation (e.g. Monte Carlo)Parallel Random Number Generation 結(jié)合開源R New in v7.3PEMA-R APIrxDataSteprxExecCopyright Microsoft Corporation. All rights reserved. 47微軟R-Server提供大量的算法和函數(shù)

34、MICROSOFT CONFIDENTIALData Warehouse LayerRaw Data LayerSQL Integration ServicesData Analysis LayerSQL Analysis ServicesSQL Database ServicesData Visualization LayerPower BIn數(shù)據(jù)展現(xiàn)層，提供多樣化的報(bào)表展示應(yīng)用。相關(guān)組件：Reporting Service / Datazen / PowerBIn數(shù)據(jù)分析層，提供數(shù)據(jù)建模、多維分析，數(shù)據(jù)挖掘等多種功能，優(yōu)化查詢性能。相關(guān)組件：Analysis Servicesn數(shù)據(jù)倉庫層，

35、從各個(gè)數(shù)據(jù)源集成數(shù)據(jù)，清洗數(shù)據(jù)，并存儲(chǔ)數(shù)據(jù)做進(jìn)一步處理相關(guān)組件：Database Engine，Integration ServicesMobile SolutionReporting Service微軟提供多樣化的BI展示方式MICROSOFT CONFIDENTIAL微軟不斷增強(qiáng)Mobile BI的功能Reporting ServicesSharepointOnlineAnalysis ServicesData WarehouseStream InsightData WarehouseCrawlerETLSensorsDevicePower BIWeb ReportingApp ToolI

36、aaSPaaSSaaSApp on AzureMICROSOFT CONFIDENTIALMobile BIMICROSOFT CONFIDENTIAL微軟PowerBIMICROSOFT CONFIDENTIAL客戶案例The Connected Marketing, Sales & ServiceOthersThe Connected VehicleConnected Product InnovationConnected OperationsTransformation OpportunitiesCustomer ExamplesMICROSOFT CONFIDENTIAL微軟在汽車行業(yè)

37、的客戶和合作伙伴Delivering core technology platforms and solutions for over thirty yearsProduct Development and InnovationGlobalOperationsTelematics 2.0 and the Connected Car Marketing, Sales and Service 53MICROSOFT CONFIDENTIALGPSTCU遠(yuǎn)程控制單元遠(yuǎn)程控制單元汽車總線大數(shù)據(jù)集群大數(shù)據(jù)集群高速采集服務(wù)器高速采集服務(wù)器車輛配置信息實(shí)時(shí)總線數(shù)據(jù)GPS數(shù)據(jù)3G3G移動(dòng)網(wǎng)絡(luò)移動(dòng)網(wǎng)絡(luò)1.車輛遠(yuǎn)程跟蹤診斷系統(tǒng)實(shí)時(shí)監(jiān)控實(shí)時(shí)監(jiān)控遠(yuǎn)程指令遠(yuǎn)程指令報(bào)表分析報(bào)表分析大數(shù)據(jù)在汽車行業(yè)的應(yīng)用案例MICROSOFT CONFIDENTIAL需求新車型量產(chǎn)前，采集并保存路試車輛的行駛數(shù)據(jù)。每輛路試車輛每天產(chǎn)生的數(shù)據(jù)從50M到1G不等，取決于采集的數(shù)據(jù)類型和行駛時(shí)間。根據(jù)測(cè)試場(chǎng)景，可以遠(yuǎn)程配置需要采集的數(shù)據(jù)類型和采樣頻率。對(duì)路試車輛進(jìn)行遠(yuǎn)程實(shí)時(shí)監(jiān)控、發(fā)送測(cè)試指令、遠(yuǎn)程故障診斷和異常報(bào)警。將指定時(shí)間段的采樣數(shù)據(jù)轉(zhuǎn)換成PUMA格式文件，供研發(fā)中心對(duì)產(chǎn)品設(shè)計(jì)進(jìn)行驗(yàn)證。對(duì)采樣數(shù)據(jù)進(jìn)行分析，產(chǎn)生報(bào)表。解決方案部署