大數(shù)據(jù)分析存儲解決方案

1、從企業(yè)數(shù)據(jù)向大數(shù)據(jù)的擴(kuò)展Traditional ApproachStructured, analytical, logicalSystems of RecordNew ApproachCreative, holistic thought, intuitionSystems Of EngagementMultimediaSystems of Insight Enterprise Integrationand Context AccumulationStructuredRepeatableLinearUnstructuredExploratoryDynamicData WarehouseWeb L

2、ogsSocial DataText Data:emailsSensor data:imagesRFIDInternal App DataTransaction DataMainframe DataOLTP System DataHadoop andStreamsTraditional SourcesNew SourcesERP data具備洞悉能力的系統(tǒng)Systems of Insight對新式基基礎(chǔ)架構(gòu)構(gòu)的需求求在可靠和安安全的環(huán)境中中處理關(guān)關(guān)鍵業(yè)務(wù)務(wù)應(yīng)用存取和處處理海量數(shù)據(jù)據(jù)包括結(jié)構(gòu)構(gòu)化和非非結(jié)構(gòu)化化數(shù)據(jù)速度及時時響應(yīng)隨隨時可能能出現(xiàn)的的商業(yè)機(jī)機(jī)會，這這就需要要靈活、實(shí)時性性的基礎(chǔ)礎(chǔ)架構(gòu)

3、ThedynamicsofSoR andSoE:通過負(fù)載載及資源源部署的的優(yōu)化，來增強(qiáng)強(qiáng)靈活性性和效益益通過采用用包括基基于開放放標(biāo)準(zhǔn)的的技術(shù)等等新技術(shù)術(shù)來改善善ITeconomicsSystemofRecord（SoR）Systems of Engagement（SoE）對的決策策對的地方方對的時間間點(diǎn)BigData& Analytics大數(shù)據(jù)分分析的新新型架構(gòu)構(gòu)解決方方案IBMBig Data&AnalyticsInfrastructureData ZoneApplicationZone4SmartMeteringGrid Operations電網(wǎng)管理理FieldService外勤現(xiàn)場場服

4、務(wù)ResourcePlanning資源規(guī)劃劃CustomerService /CustomerOperations實(shí)現(xiàn)真正正的有效效的法規(guī)規(guī)遵從及時發(fā)現(xiàn)現(xiàn)能源損損耗問題題、以及及偷電和和欺詐行行為提高客戶戶滿意度度電量使用用預(yù)測更更為精確確電網(wǎng)運(yùn)維維優(yōu)化減少停電電次數(shù)和和時間案例:SmartMetering智慧電力力計(jì)費(fèi)大數(shù)據(jù)分分析應(yīng)用用可以帶帶來真正正的業(yè)務(wù)務(wù)價值法規(guī)遵從從案例:用大數(shù)據(jù)據(jù)分析來來加強(qiáng)SmartMetering數(shù)據(jù)分析析的高可可用性，以確保保隨時了了解用戶戶喜好跨應(yīng)用的的TB級的數(shù)據(jù)據(jù)需求通用虛擬擬化存儲儲平臺實(shí)時收集集、存儲儲并分析析數(shù)據(jù)，最快可可達(dá)50,000datapo

5、ints/sec歷史用電電狀態(tài)數(shù)數(shù)據(jù)的復(fù)復(fù)雜查詢詢處理數(shù)據(jù)在加加載到數(shù)數(shù)據(jù)倉庫庫前的清清洗、驗(yàn)驗(yàn)證，這這些數(shù)據(jù)據(jù)可能來來自很多多的用戶戶、收費(fèi)費(fèi)系統(tǒng)或或斷電保保護(hù)系統(tǒng)統(tǒng)關(guān)系掌控控構(gòu)建和維維護(hù)電網(wǎng)網(wǎng)的唯一一試圖對整個企企業(yè)的結(jié)結(jié)構(gòu)化和和非結(jié)構(gòu)構(gòu)化數(shù)據(jù)據(jù)t做全局導(dǎo)導(dǎo)覽Navigation，從中發(fā)發(fā)現(xiàn)Discover價值分析用戶戶用電情情況，偵偵測偷電電、改表表等行為為預(yù)測哪些些用戶適適合于哪哪些分時時時段電電價或需需求/響應(yīng)服務(wù)務(wù)分時時段段電價的的實(shí)時定定價或或提供及時時的需求求/響應(yīng)服務(wù)務(wù)IBMBig Data&AnalyticsReference ArchitectureBigDataPlat

6、formCapabilitiesInformationIngestReal-timeAnalyticsWarehouse&Data MartsAnalyticAppliancesAllDataSourcesAdvancedAnalytics/NewInsightsNew/EnhancedApplicationsCognitive認(rèn)知Learn Dynamically?Prescriptive 規(guī)范Best Outcomes?Predictive預(yù)測What Could Happen?Descriptive描述What Has Happened?Exploration and Discovery

7、What Do You Have?Streaming DataText DataApplications DataTime SeriesGeo SpatialRelationalSocial NetworkVideo & ImageAutomated ProcessCase ManagementAnalytic ApplicationsWatsonCloud ServicesISV SolutionsAlertsNewInfrastructureLeverages DataTypesData inMotionData atRestData inMany FormsInformationInge

8、stionand Operational InformationDecisionManagementBIandPredictiveAnalyticsNavigationandDiscoveryIntelligenceAnalysis Raw Data Structured Data Text Analytics Data Mining Entity Analytics Machine LearningLanding Area, Analytics Zone and ArchiveVideo/AudioNetwork/SensorEntityAnalyticsPredictiveReal-tim

9、eAnalyticsExploration,Integrated Warehouse,and MartZonesDiscoveryDeep ReflectionOperationalPredictiveStreamProcessingData IntegrationMasterDataStreamsInformationGovernance,SecurityandBusinessContinuityBigInsightsStreamsWarehouseInfoSphereBigInsightsHadoop-based低延遲分分析，針針對多樣樣化的、海量靜靜態(tài)數(shù)據(jù)據(jù)Data-At-RestNet

10、ezzaHigh Capacity Appliance基于結(jié)構(gòu)構(gòu)化數(shù)據(jù)據(jù)的可查查詢歸檔檔Netezza1000基于結(jié)構(gòu)構(gòu)化數(shù)據(jù)據(jù)的BI+定制化分分析DataSmartAnalyticsSystem基于結(jié)構(gòu)構(gòu)化數(shù)據(jù)據(jù)的運(yùn)營營分析InformixTimeseriesTime-structuredanalyticsInfoSphereWarehouse基于結(jié)構(gòu)構(gòu)化數(shù)據(jù)據(jù)的大容容量數(shù)據(jù)據(jù)分析InfoSphereStreams低延遲流流數(shù)據(jù)分分析Velocity,Variety& VolumeData-In-MotionMPPDataWarehouseStreamComputingInformation

11、IntegrationHadoopInfoSphereInformationServer海量數(shù)據(jù)據(jù)集成和和轉(zhuǎn)化Apache Hadoop:跨服務(wù)器集群的大數(shù)據(jù)集分布式處理開放系統(tǒng)框架，采用的是一種簡單化編程模型IBMBig DataPlatform大數(shù)據(jù)平平臺What:一種開源源軟件，將數(shù)據(jù)據(jù)計(jì)算分分布到整整個集群群的常見見商用服服務(wù)器和和存儲上上Why:傳統(tǒng)的計(jì)計(jì)算架構(gòu)構(gòu)是一種種沿縱向向擴(kuò)展模模式，通通過更快快的SAN、大容量量內(nèi)存和和多級緩緩存將數(shù)數(shù)據(jù)加載載到CPU上，成本本比較高高。What:Hadoop把大數(shù)據(jù)據(jù)集合拆拆分區(qū)劃劃為小數(shù)數(shù)據(jù)集合合，再把把小數(shù)據(jù)據(jù)集合分分發(fā)到多多臺普通通服

12、務(wù)器器上，是是一種橫橫向擴(kuò)展展模式。Why: Scalable,Flexible,CostEffective, FaultTolerentComponents:MapReduce,HDFSWhat isHadoop?NameNode (Metadata store)NodesHDFS ClusterOperating SystemNodesElastic Storage -SNC ClusterKernel LevelIBMValueforHadoop!HDFS把數(shù)據(jù)分分散存儲儲在多個個存儲節(jié)節(jié)點(diǎn)Node上HDFS設(shè)計(jì)時就就假設(shè)存存儲節(jié)點(diǎn)點(diǎn)有失效效的可能能，所以以HDFS會把一份份數(shù)據(jù)復(fù)復(fù)制3

13、份以上，分散存存儲在多多個節(jié)點(diǎn)點(diǎn)上，從從而實(shí)現(xiàn)現(xiàn)系統(tǒng)整整體上的的可靠性性HDFS文件系統(tǒng)統(tǒng)是由服服務(wù)器節(jié)節(jié)點(diǎn)集群群組成的的，每臺臺服務(wù)器器依照HDFS的特有block協(xié)議支持持網(wǎng)絡(luò)化化block數(shù)據(jù)HDFS NameNode有發(fā)生單單點(diǎn)故障障的危險險IBM在改善文文件系統(tǒng)統(tǒng)的性能能同時消消除了單單點(diǎn)故障障Elastic Storage-SNC(available as betacode)Hadoop說明, MapReduce, HDFSHadoopStackWhat doesitlooklike?典型Hadoop存儲的Pain Points在選擇HDFS的組件（如軟件件、服務(wù)務(wù)器、網(wǎng)網(wǎng)絡(luò)和存存

14、儲等）時很難難選對在從測試試環(huán)境遷遷移到生生產(chǎn)環(huán)境境時，需需要做的的調(diào)優(yōu)和和調(diào)整工工作太繁繁復(fù)了長期持續(xù)續(xù)不斷的的運(yùn)維保保障過于于繁重，比如老老要更換換失效組組件（尤尤其是硬硬盤），這使得得保證期期望的SLA非常難CPU和存儲去去耦本來用戶戶的CPU和內(nèi)存已已經(jīng)滿足足計(jì)算需需求，但但為了存存儲容量量需要安安裝更多多的硬盤盤不得不不買更多多的、不不必要的的CPU和內(nèi)存Storage optionsavailable havecleargaps本地存儲儲的利用用率低(25%)，每次需需要擴(kuò)容容的時候候就要添添加更多多的服務(wù)務(wù)器，而而一旦硬硬盤失效效后需要要重建，服務(wù)器器越多，失效的的幾率越越高，性

15、性能也就就越差I(lǐng)BMStorageforHadoop傳統(tǒng)的Hadoop集群使用用的是服服務(wù)器內(nèi)內(nèi)置硬盤盤存儲。如果用用作測試試或科學(xué)學(xué)研究還還好，可可作為業(yè)業(yè)務(wù)運(yùn)行行的存儲儲就要采采用企業(yè)業(yè)存儲Hadoop集群要負(fù)負(fù)責(zé)數(shù)據(jù)據(jù)保護(hù)和和復(fù)制重建（就就是copy）失效的的數(shù)據(jù)集集到不同同節(jié)點(diǎn)上上嚴(yán)重影響響CPU性能，無無法實(shí)現(xiàn)現(xiàn)企業(yè)級級的RASReplicatedata問題同上上擴(kuò)展的時時候同時時增加處處理器/網(wǎng)絡(luò)/存儲，無無法做到到物盡其其用（nowaytoseparatethese3even if excesscapacityexistinginone(e.g.Needed morestorag

16、ebuthad to addCompute andNetwork)）使用外部部存儲可可以將存存儲負(fù)載載和Hadoop計(jì)算節(jié)點(diǎn)點(diǎn)分離，同時還還獲得了了企業(yè)存存儲的好好處。Sell thevalueofXIV, V7000,SVC, etc.用戶一般般會隨HadoopFileSystem部署；采采用Elastic Storage可以有很很多好處處14數(shù)據(jù)加速速Experience theinstant resultsthatcome fromIBM FlashSystemDriveasmuch as45Xfasteranalytics resultsoncertainworkloads數(shù)據(jù)負(fù)載載的

17、多樣樣性和靈靈活性XIVdeliverspredictableperformancethatscaleslinearlywithouthotspotsdelivering insights fromanalytics fasterwith tuning-free datadistributionScale-out, parallel processingofElasticStorage software andintegrationwith FlashSystem dramaticallyacceleratesperformanceofAnalyticsclustersVirtual Stor

18、ageCenter withSVC automaticallyoptimizes datawarehouse performance andcost acrossFlashandDiskMainframeDataEnvironmentsIntegrationwith DB2& specialtyanalytics“engines”leveraging DS8870delivers4xreductioninbatchtimeswithnewHighPerformanceFlashEnclosuresHigh speed encryptiononeverydrivetypesecures data

19、數(shù)據(jù)保護(hù)護(hù)和保留留LTFS EE w/ tapeprovidesreducedTCObyupto90%over diskfor longtermretentionofdataatrest withalargeopen formattape repositoryReducethe amountofdata to be storedbyupto25timeswith ProtecTIERde-duplication12x更快IBMFlashSystemincreasedSPLUNK &SAS application efficiencytoperformbusinessanalytics20 x改

20、善inactionable supplychainanalytics,4xreductioninbatchtimes, virtualization forplug &play6x時間節(jié)省省“GPFSallowsustomovethemetadatafromthedisktotheFlashSystemonline. Oncewedid that, thebackups werereduceddown to about an hour.”2 hrsbecomes2 minutes失效切換換時間大大幅縮短短Mapping CharacteristicstoIBMStorageProductsSt

21、orage Infrastructure需求適用于所所有的5種應(yīng)用場場景OptimizedMulti-TemperatureWarehouse優(yōu)化的多多級存儲儲庫AllFlashFlashSystemHybridDS8000EasyTierXIV+SSDCachingStorwizeEasyTierFlashSystemSolution(VSC +FlashSystem)PureSystemsPureFlex(XIV orStorwizew/EasyTier)PureDataforTransactions (Storwize)PureDataforAnalytics (Netezza)Midr

22、ange& EntryTier 0AccelerationSmarter StorageIntegrated SystemsEnterpriseOfferingsXIVzEnterpriseSolutionsforAnalytics withDS8000PureDataSystemforOperationalAnalyticswith StorwizePureFlexSystemwith StorwizeDS8000SmartAnalyticsSystems withDS3xxxOpen &ExtensibleStorwizefamilyFlashSystemfamilyIBMSmarterS

23、torage的設(shè)計(jì)就就是支持持大數(shù)據(jù)據(jù)分析高效和優(yōu)優(yōu)化數(shù)據(jù)據(jù)基礎(chǔ)架架構(gòu)IBMFlashSystem：為大數(shù)數(shù)據(jù)分析析應(yīng)用設(shè)設(shè)計(jì)的，讓應(yīng)用用和數(shù)據(jù)據(jù)實(shí)現(xiàn)極極速IBMFlashSystem的極速性能能讓實(shí)時業(yè)業(yè)務(wù)決策策成為可可能適合于模模塊化數(shù)數(shù)據(jù)存儲儲結(jié)構(gòu)的的Hadoop系統(tǒng)。某某些或所所有數(shù)據(jù)據(jù)可以保保存到Flash閃存上，其他可可以保存存到XIVIBMXIV: Optimizeddata workload diversityforBig Data&AnalyticsIBMXIV的高性能無須人工工干預(yù)配配置，且且適用于于各種各各樣的存存儲負(fù)載載IBMXIV的效率高的異乎乎尋常，而且簡簡單性業(yè)業(yè)

24、內(nèi)最高高，內(nèi)置置友好界界面IBMXIV的彈性是企業(yè)級級的，完完全保證證了數(shù)據(jù)據(jù)的可用用性和業(yè)業(yè)務(wù)連續(xù)續(xù)性XIV:為Analytics而生無與倫比比的性能可擴(kuò)展的的網(wǎng)格存存儲架構(gòu)構(gòu)任意時間間支持任任意讀寫寫負(fù)載板上的閃閃存Flash無與倫比比的可靠性精致的數(shù)數(shù)據(jù)分布布無雙的磁磁盤重建建時間企業(yè)級的的可用性性無與倫比比的簡易性簡單的規(guī)規(guī)劃、供供給和靈靈活性上線后零零維護(hù)零調(diào)優(yōu)“XIV最吸引我我們的地地方就是是其超強(qiáng)強(qiáng)的性能能we正是由于于XIV為我們的的精細(xì)復(fù)復(fù)雜的分分析應(yīng)用用提供了了一致的的高性能能，使使得我們們能夠?yàn)闉槲覀兊牡挠脩魩砀喽嗟膬r值值。”SAS和XIV網(wǎng)格架構(gòu)構(gòu)完美的結(jié)結(jié)合大規(guī)

25、模并并行計(jì)算算保持持續(xù)續(xù)地最佳佳性能BalancedPerformance性能均衡衡常年零調(diào)調(diào)整Unprecedented Scalability史無前例例的擴(kuò)展展性配合添加加SAS節(jié)點(diǎn)和XIV模塊即可可IBMSVC: Optimizeddata workload flexibility forBigData& AnalyticsIBMSVC通過如下下功能在在IBM大數(shù)據(jù)產(chǎn)產(chǎn)品線上上增加了了靈活性：完整和數(shù)數(shù)據(jù)虛擬擬化和數(shù)數(shù)據(jù)移動動性高級集群群和復(fù)制制多路鏡像像，readpreferredoptionReal TimeCompression實(shí)時壓縮縮Easy TierHot Extentcac

26、hingStorwizeV7000/UIBMSVC設(shè)計(jì)原則則Real-TimeCompression實(shí)時壓縮縮是設(shè)計(jì)計(jì)來做：作用于ActivePrimaryData專用的壓壓縮平臺臺Platformhandles ALLheavylifting associatedwithcompression不會影響響性能Wemodifyacompressed filein-placeefficiently不會改變變用戶應(yīng)應(yīng)用Usersnoradmins needtochange anything處理流程程不變壓縮是在在線完成成，不是是事后壓壓縮業(yè)界標(biāo)準(zhǔn)準(zhǔn)壓縮算算法所采用的的壓縮算算法已經(jīng)經(jīng)使用了了幾十年年

27、StorwizeV7000/UIBMSVC24流處理計(jì)計(jì)算& IBMFlashSystemsData:是擁有還還是保存存?或是是分分析和開開始行動動!Data inData at25InfoSphereStreams:大數(shù)據(jù)流流分析為分析動動態(tài)數(shù)據(jù)據(jù)而建多并發(fā)輸輸入數(shù)據(jù)據(jù)流大規(guī)?？煽蓴U(kuò)展Massive scalability分析和處處理的數(shù)數(shù)據(jù)多樣樣化Structured,unstructured, video,audioAdvancedanalyticoperators自適應(yīng)實(shí)實(shí)時分析析With DataWarehousesWith HadoopSystemsCurrent factfind

28、ing當(dāng)前數(shù)據(jù)據(jù)查詢分許流動動中的數(shù)數(shù)據(jù)在數(shù)據(jù)落落盤前低延遲模模式, pushmodel數(shù)據(jù)驅(qū)動動真正的數(shù)數(shù)據(jù)分析析Historical factfinding歷史數(shù)據(jù)據(jù)查詢查找和分分析存儲儲在磁盤盤上的數(shù)數(shù)據(jù)信息息批處理模模式, pullmodel查詢驅(qū)動動: submitsqueriestostaticdataTraditionalComputingStreamComputing流數(shù)據(jù)計(jì)計(jì)算代表表著計(jì)算算模式的的變遷Real-timeAnalyticsReal TimeAnalytics實(shí)時分析析想象一下下你如何何用防火火栓喝水水來自多個個多樣輸輸入源的的大量數(shù)數(shù)據(jù)直接處理理和過濾濾數(shù)據(jù)，

29、而不必必存儲僅保存有有價值的的數(shù)據(jù)僅關(guān)聯(lián)對對數(shù)據(jù)最最感興趣趣的用戶戶隨著數(shù)據(jù)據(jù)信息的的產(chǎn)生采采取行動動AdaptiveAnalytics自適應(yīng)分分析Data in MotionandDataatRest的集成1.Data Ingest數(shù)據(jù)集成成，數(shù)據(jù)挖掘掘，機(jī)器學(xué)習(xí)習(xí)，統(tǒng)計(jì)建模模實(shí)時和歷歷史數(shù)據(jù)據(jù)洞察力力的可視視化3.AdaptiveAnalyticsModel數(shù)據(jù)收取取，在線分析析準(zhǔn)備，模式校校驗(yàn)Data2.Bootstrap/EnrichControl flowInfoSphereBigInsights, Database &WarehouseInfoSphereStreamsAdapti

30、veReal-TimeAnalytics自適應(yīng)實(shí)實(shí)時分析析來自多個個多樣輸輸入源的的大量數(shù)數(shù)據(jù)過去、現(xiàn)現(xiàn)在和未未來全方方位綜合合性視圖圖實(shí)時分析析，低延延時結(jié)果果Full contextfor deepanalysis深度分析析的完整整的上下下文跨data in motionanddataatrest的常用數(shù)數(shù)據(jù)分析析自適應(yīng)-隨機(jī)而變變當(dāng)發(fā)現(xiàn)非非預(yù)期行行為時，自適應(yīng)應(yīng)當(dāng)識別出出新數(shù)據(jù)據(jù)意義時時深度分分析之開始沒有有意識到到的數(shù)據(jù)據(jù)意義，隨后才才可能意意識到自適應(yīng)在開始沒沒有意識識到的，隨后可可以找出出數(shù)據(jù)模模式StockmarketImpactofweatheronsecurities pri

31、cesAnalyze marketdata at ultra-lowlatenciesMomentumCalculatorFraudpreventionDetectingmulti-partyfraudReal timefraudpreventione-ScienceSpaceweather predictionDetectionoftransient eventsSynchrotronatomicresearchGenomic ResearchTransportationIntelligenttraffic managementAutomotiveTelematicsEnergy&Utili

32、tiesTransactivecontrolPhasorMonitoring UnitDown holesensor monitoringNatural SystemsWildfiremanagementWatermanagementOtherManufacturingText AnalysisERPfor CommoditiesReal-time multimodal surveillanceSituational awarenessCyber security detectionLaw Enforcement, Defense & Cyber SecurityHealth & Life S

33、ciencesICU monitoringEpidemic early warning systemRemote healthcare monitoringTelephonyCDR processingSocial analysisChurn predictionGeomapping如何使用用InfoSphereStreams?加快數(shù)據(jù)據(jù)流入分分析系統(tǒng)統(tǒng)的速度度向交易方方向加速速。一個高效效和靈活活的基礎(chǔ)礎(chǔ)架構(gòu)顯顯然可以以加快流流速，并并平衡不不同數(shù)據(jù)據(jù)分析的的需求CoresSCMStorageNetworkCoresSCMStorageNetworkCoresSCMStorageNetwor

34、kCoresSCMStorageNetwork+預(yù)測分析數(shù)據(jù)倉庫文本分析Hadoop Workloads優(yōu)化敏感性分析加快流速價值時間“觸發(fā)事件”數(shù)據(jù)完備交易Insight預(yù)見獲取數(shù)據(jù)時間分析數(shù)據(jù)時間行動時間大數(shù)據(jù)分分析的新新式基礎(chǔ)礎(chǔ)架構(gòu)解解決方案案IBMBig Data&AnalyticsInfrastructureData ZoneApplicationZoneExperience real-timeanalytical insights withupto50 xbetter performancethan enterprisedisksystems using IBMFlashCore

35、technologyPreserveandprotectinfrastructurecontinuity while scalingtoover2petabyteofeffectiveall-flash capacity under asingle integrateinterfaceDeliver agilityand dataeconomics with4xgreater capacityinless rackspacethancompetitiveall-flashproductsSynchronizedand ComplimentarytoOverarchingStorageMessa

36、ging-Accelerate timetoinsightsthroughdatawithout borders.IBMinnovationfreesdata withagileand simpletousestoragesolutionsdeliveringsuperiordata economicsIBMFlashSystemCore LaunchMessagingDrivea complete paradigm shift in EnterpriseStoragewith theallnew IBMFlashSystemFamilyIBMFlashSystemFamily2015 The

37、meTime to insight. Timetovalue. Timetomarket.IBMFlashSystem, itsabouttime.FlashRealized!IBMFlashSystemV9000FoundationalPillarsIBMFlashCoreTechnology is theDNAofthe FlashSystem FamilyScalable PerformanceEnduring EconomicsAgile IntegrationIntroducingtheNew IBMFlashSystemFamilyOfferingsIBMFlashSystem90

38、0Extreme Performance:Delivers100microsecondresponsetimesMacroEfficiency:Lowestlatencyofferingwith40% greatercapacityatalowercost percapacityEnterprise Reliability:IBMenhancedMicron MLCflashtechnology withFlashWearGuaranteePowered byIBMFlashCoreTechnologyIBMFlashSystemV9000ScalablePerformance:Grow ca

39、pacity andperformancewith up to 2.2PB scalingcapabilityEnduringEconomics:Next generationflashmediawithlowercost percapacityAgileIntegration:Fullyintegrated systemmanagement to simplify managementand improveworkforce productivityundera singlename spaceFlashSystem900IntroducingIBMFlashSystem900,thenextgeneration in ourlowestlatencyofferingIBMMicroLatencywith up to 1.1million IOPS40%greatercapacityata 1