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Data that is redundant, the same data stored in many places, is an example of unwanted data because it is excessive and demands con guration management Data that lacks con guration management where it is unreliable is unwanted Data that you buy Data that you buy may be an asset with limited shelf life That is often the case Nonetheless, it is an asset as long as it is useful Sometimes, data is maintained longer than its useful life and that absorbs extra cost Disposition of data assets deserves deliberation because sometimes data may lose its immediate value but its value may resurface as a matter of historical reference and for trend analysis and prediction Data generated within your enterprise that stays within your enterprise Some data is proprietary and must be protected with high security, accessible with credentialing and privileging rules How is this data identi ed and protected Data generated within your enterprise that is shared with others outside for free Some data should be shared freely with partners and customers Some of this needs protection from unauthorized users, such as competitors and enemies Careful consideration as a matter of routine will maximize advantage from sharing while limiting risk Data generated within your enterprise that is shared with others outside for a fee for limited use Some information is so valuable and proprietary that it is worth charging for use under licensing and other contractual terms Data generated within your enterprise that is shared with others outside for a fee for unrestricted use Some data may be licensed or shared under unrestricted use as prescribed in agreements This circumstance is where data use contributes to strengthening brand awareness or market development, or otherwise strengthens the contribution to the federated way of doing business From work on an advanced ghter program involving a multitude of customers and suppliers with varying contractual privileges, we understand the necessity to be deliberate and thorough in addressing these conditions describing data 6 Data are governed by business rules that may be contractual and regulatory Some rules are inherited or imposed, while others are invented by management Rules constrain processes, and they constrain how and where data assets are used or otherwise shared Anticipated are trends toward automated regulatory environment and automated contractual environments This is where legal and regulatory code is delivered to govern systems replacing paper documentation Anticipated is that there will be combinations of paper instructions, electronic words, and actual code for automating compliance, validation, and veri cation These things are possible with smart data
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7 Creating, receiving, processing, publishing, accessing, and storing data assets consumes resources expressed by labor to support data management as well as essential enabling technology From the latest experience, we have learned that it is essential to make certain that the organization has the right skill sets to support smart data strategy to perform all of the data processing and management routines It is essential to employ resources that have up-to-date certi cations and knowledge about essential enabling technology It is ne to leverage the current workforce; however, it is essential that they are equipped with the latest knowledge and with the most current tools and technologies to create a smart data environment Failure to keep pace is the source of excess cost and uncompetitive performance 8 Data must be engineered for smartness so that it is interoperable and secure From experience in supporting advanced weapon systems programs and logistics systems modernization for the Department of Defense, we identi ed special skills, knowledge, and pro ciency needed to implement smart data strategy In addition to routine skills such as program and project management there are additional skills needed: Integration and interoperability architect Transformation/mapping and data architect Process modeler Adapter developer Technical infrastructure services architect Librarian taxonomist Repository specialist Content editor Business case analyst Also, having appropriate domain expertise is essential for collaboration with the customer in requirements planning Figure 52 illustrates the operational solution environment Three engineering disciplines are present in the illustration: process engineering, grid engineering, and data engineering Smart services, smart grid, and smart data are products from these disciplines that are created and managed with an enterprise view The SOE paradigm was originally developed as part of the DoD Electronic Logistics Information Trading Exchange (ELITE) program The intent is to bring together the DoD s net-centric strategy and commercial service-oriented architecture (SOA) web services technology Smart data is the missing link in the DoD and government strategies, and that is how we discovered the topic It is not our intention to discuss the detailed merit of DoD strategies, although it is important to note that considerable effort is made today at implementing part of this approach Addressing the omission will help improve its success and effectiveness Here is a description of the critical terminology introduced in the gure that deserves understanding by executives because they are elements that
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