优化制造业数据交换方式 - 蓝图

Optimizing ManufacturingData Exchange Pervasive Datacenter Architecture (PDx™)BLUEPRINT PDx™ Blueprint:OptimizingManufacturingData Exchange Introduction Traditional IT architectures withinmanufacturing businesses, corporations,factories, agencies, vendors andfirms are not designed to effectivelyleverage data, optimize data exchangeor address the challenges of DataGravity. Data created from differentlines of business is often stored insilos throughout the company. Someelements on premise and some in thecloud. This distribution without intentleads to performance issues, operationaland supply chain costs, and an increasein overall complexity. Successfuldigital transformation requires a data-centric IT infrastructure that localizesdata aggregation, staging, analytics,streaming and management in centersof data exchange at global points ofbusiness presence. Fragmented architecturesburdenedby technical debt and driven bypoint solutions lack capabilities andperformance required for hybridIT workflows Inconsistent data storageand access methodslead tostorage sprawl, cost overrunsand compliance issues Implement distributed datastaging/aggregationto optimizedata exchange between users, things,networks and clouds Integrate public/private datasourcesto enable real-timeintelligence across distributedworkflows Distribute business intelligencecapabilitiesto allow you to createnew secure B2B data exchangesand unlock new opportunities Deploy regional data lakes/distributed data warehousesto maintain data performance,compliance and sovereignty Siloed dataprevents the enablementof analytics and new business modelscentered around data Cloud connectivity and networknot optimized, causes poorapplication performance whenleveraging cloud to access local data Solution Step 1 Step 3 Step 2 Implement data staging/aggregation Host data and analytics adjacent to networkingress/egress Integrate public/private data sources 1Distributed data staging/aggregation2Regionalized data storage for compliance1 3Integrated public and private data sources 4New business opportunities unlocked Action:Directly interconnect cloud on-ramps to centers ofdata storage Action:Implement a cohesive data storage strategy at centersof data exchange Action:Distribute business intelligence and connectglobal data ecosystems Step 1: Implement data staging/aggregation 1Deploy centers of datastaging in key locations2Data Lakes store raw datato be analyzed and curatedby data scientists3Refined data sits in the datawarehouse for businessprofessionals to use4Due to the value and sen-sitivity of enterprise data,access needs to be strictlycontrolled and logged Distributed data staging/aggregation Action Outcomes +Localized data improves applicationperformance and user experience1+Helps user maintain compliance anddata sovereignty Step 2: Integrate public/private data sources The Core SwitchingInfrastructure terminatesconnectivity into the DataHub and enables access tothe cloud and other datasources by direct high-per-formance interconnection Integrated public andprivate data sources Action Directly interconnect cloud on-rampsto centers of data storage. 2Additional connectivity isprovided by use of soft-ware-defined on-rampssuch as Service Exchange™ +Enable performant data exchangebetween sources and destinations+Operate deployments as a seamlessextension of global infrastructurewith consistent experience, securityand resiliency 3Other data sources can becloud storage, IaaS environ-ments, SaaS environmentsor other remote Data Hubs Outcome +Optimize data exchange between users,other devices, networks and clouds Step 3: Host data and analytics adjacent to network ingress/egress 4 GPU Farm is locateddirectly adjacent to storeddata for direct accessto enable AI Developmentand workloads New businessopportunities unlocked DATA HUB Action Bulk compute farmis used for media contentcreation, complexmodeling and simulations Distribute business intelligence andconnect global data ecosystems+Add processing, analytics andstreaming capability at global pointsof business presence+Host a B2B meeting place forcompanies to collaborate and connecttheir business platforms Outcome +Enable real-time intelligence acrossdistributed workflows locally andglobally Target state architecture Summary A purpose-built data-centric architecture to optimize manufacturingdata exchange can reduce security risks, and can lower costs as aresult of a reduction of bandwidth and duplicated infrastructure, andcan contribute to revenue growth through unbounded data analyticperformance. This is necessary to support exploding volume,variability and velocity of data creation as well as processing andstorage required to accommodate digital business. The strategybrings the users, networks, systems and controls to the data,which removes barriers of Data Gravity and creates centers of dataexchange to scale digital business. The Optimizing Manufacturing Data Exchange Bl