Smart Data Criteria Checklist in Visual Studio .NET

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TABLE 51 Smart Data Criteria Checklist
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Smart Data
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Three Dimensions
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Concept of operations (CONOPS)
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1 Enterprise context
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Operational architecture (OA)
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2 Interoperability technology
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3 Data-aligned methods and algorithms
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STRATEGY
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Old harmonization activities focused on using brittle standards that required much work to achieve synchronization within the user community Today s smart data technology leapfrogs the legacy by achieving data exchange based on open and interoperable standards and implementation conventions Service-oriented architecture describes the infrastructure, accompanied by data exchange servers that some call smart grid Enterprise services are common among the user community as a part of a shared services strategy and utility service concept Work requires metadata management and data mapping that employs speci c tools The comprehensive environment is called the service-oriented enterprise (SOE), described in earlier chapters In an exceedingly open and transparent operating environment, it is imperative to manage credentialing and privileging to ensure awless and secure data exchange, access, and use Data-Aligned Methods and Algorithms Data is associated with methods and algorithms represented by best practices and preferred uses for analysis This is accomplished via tagging Aligning methods and algorithms with data is aimed at ensuring executives have the best practices available to support planning, problem solving, decision making, sense making, and predicting Employing contemporary technology, executives can expect data to be actionable and available immediately to support analysis The smart data paradigm aims at building in analytical intelligence such that the executive depends more on automated systems and less on a large staff of analysts In this regard the smart data system is autonomic As an extended application of smart data autonomics, automated regulatory environment (ARE) and automated contracting environment (ACE) are offshoot applications Cloud Computing A computing paradigm in which tasks are assigned to a combination of connections, software and services accessed over the Internet This network of servers and connections is collectively known as the cloud Computing at the scale of the cloud allows users to access supercomputer-level power Using a thin client or other access point, like an iPhone, BlackBerry or laptop, users can reach into the cloud for resources as they need them [10] Semantic Web The Web of data with meaning in the sense that a computer program can learn enough about what the data means to process it [11] People are a strategic element, especially those possessing data Engineering disciplines Interoperable data technology includes the data engineering disciplines that are possessed by quali ed staff combined with enabling technologies software tools and hardware Strategy Elements Applying Daniel Hunter s suggestions about four aspects of effective strategy, a smart data strategy template begins as follows
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CEO S SMART DATA HANDBOOK
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1 Set Direction Describe your starting position What are the current CONOPS and OA for enterprise performance optimization employing data from the senior executive perspective Model the as-is situation Given an introduction to smart data concepts and characteristics, where do you want to be Model the to-be situation What performance outcomes do you want What do you want to change What is the current state of your data and associated assets Have data specialists perform an objective assessment 2 Concentrate Resources The chances are that much of your IT support resources are skewed to infrastructure maintenance and management This skew must be shifted to direct more resources directly to smart data vision development and direct and immediate executive support for planning, problem solving, decision making, sense making, and predicting 3 Maintain Consistency Develop a CONOPS and OA that will ensure commitment and focus on processes and mechanisms that will ensure maximum executive support for optimizing enterprise performance 4 Retain Flexibility Technology and ideas about smart data are advancing Accommodate the advance by adopting spiral development and iterative reviews Your smart data strategy must be customized to your unique enterprise and to your unique position in the total enterprise context Technical Solution and Enablement Selecting standards that are most relevant to your enterprise and ones that satisfy the criteria for openness and interoperable data exchange is a technical requirement Quali ed staf ng and profession development are critical success factors in breaking from the cycle imposed by layers of legacy barriers Having strong command of modeling techniques and analytics are critical ingredients Enterprise performance is optimized by smart data strategy through policy, goals, and actions
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52 POLICY There are many different types of policies, and even multiple policies regarding data as we have reviewed examples We are addressing a speci c policy advocating smart data ideas applied speci cally in support of executive enterprise performance optimization The intent of the policy is to address every member of the user community with regard to their credentials and privileges and rights to access, publish, distribute, use, repackage, and exchange information 1 Policy is sponsored by the CEO and owned by the enterprise You will have to tailor your policy to the needs of your executive and the needs of the enterprise When searching for examples of smart data policy, we really didn t nd many good ones
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