2026年赋能未来工业：打破数据孤岛以统一AI数据平台驱动智能制造新范式

赋能未来工业：打破数据孤岛，以统一AI数据平台驱动智能制造新范式从“中国制造”迈向“全球经营”：如何利用Snowflake

实现全球业务规模化客户背景●

团队挑战：团队高度精益，难以负担复杂的流水线与繁重的

IT

架构●

运营需求：迫切需要极简透明的管理模式，

以应对全球多区域的合规要求●

协作挑战：打破地域与生态壁垒，实现与全球合作伙伴的无缝协作5合规红线跨国数据流动面临严苛的当

地法律风险。数据孤岛生产数据与经营被牵绊，散

落在不同系统，又重又碎。市场信号北美的销售和营销反馈无法

实时指导深圳的研发，快速

响应市场反馈。3

Continuousimprovementthroughadvanced

analyticsSmartManufacturing2

Data-drivenoptimizationofproductionprocesses1

Real-time,unified

viewofshopfloordata

6SOLVECHALLENGING

MANUFACTURING

USECASESWITHSNOWFLAKE数据孤岛：传统制造业转型升级的隐形枷锁SustainabilityADASChargingNetworkElectrical

UtilitiesProduct/ValidationSystemsManufacturing

SystemsEngineering

SystemsAfter

Sales/

ServiceConnected

ProductsCustomer

SupportDirectto

ConsumerSupplyChainMobileAppMarketingCustomerProductFinanceRetailerMFGR&D

挖掘IT/OT

数据价值：消除孤岛，驱动智造变革LAYERED/Siloed

CROSS

LAYER/

integratedAnalytics

AnalyticsFinancial

AnalyticsSupplyChain&financialImplicationsofchangesinmanufacturingprocessPredictionofbehaviourofisolatedsensors“ScadaAnalytics”,

ERPEarlyWarningforqualitydeviationsFinancialimplicationsofproductionprocesschangesMachineOptimizationPerformanceMetricsAnalytics

… TheAIImperativeforManufacturing

Enterprise

AI

OperationsOT

Data,SensorsWarranty

ClaimsSupply

ChainSalesandDistributionQuantitativeAnalyticsCompliance

&

ESG

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CauseDiagnosticsIATF

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Defect

ProgramsDashboardDeploymentSupplierAnalyticsUnstructured

DataStructured

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assets

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PredictionIngestGovernPlant AI落地是否意味着极高的复杂度？我们是否必须拥有一支庞大的编程专家团队，才能让AI运转起来？

大模型产生的‘幻觉9怎么办？在容错率为零的车间现场，我们如何确信AI给出的指令是安全且准确的？ AI真的懂工业吗？如果数据缺乏语义上下文，AI看到的只是冰冷的数字，而非真实的生产业务。常见顾虑UNDERSTANDS

SNOWFLAKEHasthe

latestknowledgeofyourspecificdatacatalog:databases,schemas,tables,semanticmodelsand

moreISCONTEXTAWAREKnowswhereyou

areinthe

UI,whatdatayou'reworkingwith,and

retainsyourconversationalhistoryasyou

navigateAUTOMATESCOMPLEXTASKSIntelligentlyoptimizesyourrequeststosolvereal

jobs,frombuildingan

applicationtomanagingcost

orgoverningdataISSECURE

BYDESIGNAdherestoSnowflakeRBAC,ensuring

itonlyseesand

actsonthedataandobjectsyouhave

access

toTheGameChanger#1:CortexCodeSnowflake-nativeAIcodingagentINTELLIGENCERELEVANCEEFFICIENCYGOVERNANCE11CortexCode

理解整合来自车间的物理信号（Sensor）与业务流程（SAP）之间的逻辑关系

TheGameChanger#2:SnowflakeIntelligenceTransformmaintenanceoperationswithAI-powered

insightsfromyourenterprisedata●

EmpoweruserswithaunifiedAI-driven

interfacetoseamlesslyaccessinsightsfromallenterprisemaintenancedatasources.●

Eliminatemanualorchestrationtoretrieverelevantinformationfromstructuredorunstructured

datasources●

Reducetimetoresponse

with

multipleAPIcallscombinedinto

a

singlerequestandresponseCortexSearchCortexAnalystCortexSearch器imt

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/

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…MaintenanceDataDocumentAIHand-WrittenReportsHowcanIhelp?Streamlit:

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AgentWhatquestionscan

Iask?Semantic

ViewQuestionIoTSensorsCMMSBlog

引入Snowflake

Intelligence：重塑您5Why

根因溯源工作TheGameChanger#3:AutomaticSemanticModelGenerationAutomaticallygeneratessemanticmodelsusingcontextfromdashboards,queriesandexternalsemanticlayersWHY

USE

IT●

Reduces

monthsofmanualmodellingworktominutes●

Speedsupsetupofgovernedanalytics●

HelpsstandardizeandscaleenterpriseGotoSnowsight→CortexAnalyst

→ModelLetAI

inferandpopulatemodelusing

existing

contextReviewandvalidatethegenerated

modelHOWTO

USE

ITWHAT

IS

ITCreateSemanticinsights●●●15开启这场征程，需要领导层坚定不移的支持任何实质性的进步都需要持续的投入与耕耘秉持“勇于实验、不断学习、快速推广”的实战心态管理者必须躬身入局，成为变革的倡导者，引领整个组织