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Data to Customers When we talk about data to customers and attempt to do this from the viewpoints of government and commercial enterprise, the subject can become confusing The government can be a customer The government can ll the need as a trading partner Prime producers of goods and services can be customers to suppliers and vendors, both of which can serve government customers Data sharing among them is symbiotic and smart data strategy serves all Toyota Joins American Rivals, Urges Aid to US Parts Makers, is a Washington Post, march 12, 2009 headline by Kendra Marr The story is that all prime auto producers are concerned about getting capital to suppliers to sustain their viability: 20 30 suppliers can bring down an industry unless they have suf cient capital Auto suppliers don t get paid for 40 60 days on average So, in this example, the prime producers are the customers and they typically inform suppliers well in advance about their production schedules via an enterprise resource planning mechanism Suppliers likewise inform prime producers about their status and in this instance they are saying they don t have suf cient capital to stay a oat to support future orders that are coming in reduced numbers In today s environment, prime producers are informing government about the threat to their viability such that the government now becomes a factor as a trading partner with industry The ultimate customer, auto consumers, are hearing this scenario and this fuels their concerns: they may perceive greater risk associated with a major capital purchase at a time when capital is king Of course, in rosier times, data goes to commercial consumers from marketers via multimedia channels, increasingly digital media Consumers are buying more via electronic commerce and are receiving more information via directed channels over which consumers have increasing control Google permits customers to tailor their advertising channel such that they receive and have access to only what they want pull versus push Smart data strategy in the advancing new digital economy will become an increasingly important success factor Data to Suppliers Prime producers provide information to suppliers Government customers provide data to supply chains Industrial viability is increasingly dependent on governments industrial policies formal or defacto Data to Regulators or Legislators New transparency will likely result in greater demand for data from regulators; trouble in the past was that data calls are costly, redundant, or unreliable and not actionable Smart data will enable automated regulation and governance. azure web app pdf generation Micro Services with Azure Functions — PDF Download — DotNet Core
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vb.net read pdf file text 23 Nov 2018 ... Azure Functions 2.0 is production ready and capable of handling your ... This function uses external engine to PDF generation – JsReport and ... c# print multi page tiff x(t + 1) . x(t) 4/26/1999 y(t) 8 725 35 40 8 4 x(t) Data to Stakeholders Stakeholders of all kinds have greater access to data, some that is pushed to them and some that is available to pull Smart data applied to communities of stakeholders will likely strengthen relationships Data to Partners and Allies Data to partners and allies will be managed via credentialing and privileging relationships Smart data is an enabler to trusted relationships Smart Data Criteria In 4 we described how smart data has three dimensions Table 51 is a checklist summarizing the evidence of smart data There are two basic elements: concept of operations (CONOPS) and operational architecture (OA) Concept of Operations (CONOPS) Enterprise context describes the CONOPS By this we mean the executive will lead the charge to optimize performance in an enterprise context, subordinating traditional stovepiped systems engineering approaches to those that consider enterprise-wide performance and impact Enterprise scope for performance optimization will be documented in policy that is unique to the enterprise and will likely append the balanced scorecard or equivalent It most surely will be augmented by six sigma and other quantitative initiatives Smart data strategy greatly improves data actionability and transparency and revolutionizes performance management in both operational and technical dimensions Executive users are prime smart data customers and their visible use and dependency on supporting the enterprise performance optimization system (EPOS) is statement enough about commitment However, system management and governance requires hands on management The enterprise performance management process is proprietary to the enterprise and is the source of competitive advantage and superior performance Nothing else in the enterprise trumps it as a central source of enterprise knowledge Fully attributed process models are evidence of completion An operational system is evidence of practice The fully attributed process is modeled with contributions from functional management and subject matter experts facilitated by quali ed modelers and technical specialists Operational Architecture (OA) OA is a description of the technical elements needed to implement and operate the CONOPS There are four categories of technology enablement for smart data: (1) data interoperability technology, (2) data-aligned methods and algorithms, (3) cloud computing, and (4) semantic web Data Interoperable Data Technology Smart data is differentiated with modeldriven data exchange This requires the ability to model processes and data, and to strategically select standards for neutral data exchange Such selection is performed in an enterprise context and therefore requires communication with all of the critical enterprise touch points from customers, suppliers, and other appropriate stakeholders Some describe this as a harmonization activity. y(t + 1) 10/30/1995 azure ocr pdf Protected PDF readers for Microsoft Information Protection ...
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