37 lines
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4.5 KiB
HTML
37 lines
No EOL
4.5 KiB
HTML
<html xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" xml:lang="en-US">
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<head>
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<title>Designing and Building Enterprise Knowledge Graphs</title>
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<link href="../styles/page-template.xpgt" rel="stylesheet" type="application/vnd.adobe-page-template+xml"/>
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<meta content="urn:uuid:81982e4f-53b2-476f-ab11-79954b0aab3c" name="Adept.expected.resource"/>
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</head>
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<body epub:type="bodymatter">
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<section epub:type="chapter">
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<h1 class="chno" epub:type="title"><span epub:type="pagebreak" id="page_133" title="133"/>CHAPTER 6</h1>
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<h1 class="chtitle" epub:type="title">Conclusions</h1>
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<p class="noindent">It’s time to evolve the way we manage enterprise data! We need:</p>
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<p class="bbull">• to bridge the data-meaning gap between data producers and data consumers;</p>
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<p class="bbull">• data consumers’ and business users’ way of thinking about the world to be first-class citizens;</p>
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<p class="bbull">• the business concepts and relationships to be connected with the inscrutable application-centric relational databases; and</p>
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<p class="bbull">• to connect the data and metadata across an entire organization.</p>
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<p class="indent">Knowledge graphs accomplish these goals.</p>
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<section>
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<h2 class="head2" id="ch6_1">6.1<span class="space3"/><span epub:type="title">IT’S ALL A GRAPH!</span></h2>
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<p class="noindent">Everything is connected. Business concepts are connected with other business concepts. Disparate data sources can be linked together. The natural way of accomplishing these connections are through graphs. Thinking about RDF graphs versus property graphs is moot until you acknowledge that it is all a graph, and even then there is a lot of work (e.g., modeling your data as a graph) that is largely independent of your choice between the two graph models. The approach to designing and building knowledge graphs that we have presented in this book is applicable to both RDF and property knowledge graphs.</p>
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</section>
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<section>
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<h2 class="head2" id="ch6_2">6.2<span class="space3"/><span epub:type="title">MAPPING PATTERNS</span></h2>
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<p class="noindent">The connections between relational databases and knowledge graphs need to be accomplished in principled manner. Mapping patterns are a mechanism to apply reusable templates that solve a commonly occurring problem in order to prevent issues that may cause problems down the line.</p>
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</section>
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<section>
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<h2 class="head2" id="ch6_3">6.3<span class="space3"/><span epub:type="title">YOU NEED A DATA TEAM</span></h2>
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<p class="noindent">Success of designing and building a knowledge graph through an agile methodology depends on having a data product manager leading a team of knowledge scientists—data professionals with a broad set of technical and social skills. The data teams need to take responsability of <span epub:type="pagebreak" id="page_134" title="134"/>the data. Such people may be hard to find, and in our experience potential candidates have a technical background in data (SQL developers, etc.), know data modeling (UML, etc.), enjoy creating documentation, and regularly interact with business users. If looking internally, they are employees who have been at the organization for a long time and understand how the business functions. Potential candidates have dual backgrounds in computer science and arts (literature, music, etc.). The knowledge scientist serves as a communication bridge between data producers and data consumers to understand the meaning of data.</p>
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</section>
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<section>
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<h2 class="head2" id="ch6_4">6.4<span class="space3"/><span epub:type="title">BE AGILE, START SMALL, DON’T BOIL THE OCEAN</span></h2>
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<p class="noindent">It can sometimes take awhile to get the ball rolling but once data consumers see the first bits of understandable data they get excited and want more. Data consumers are empowered to ask questions that they had not even considered before with the status quo process. The agile process enables quickly adding more data in a way that data consumers can understand and easily access. The business benefit can be seen quickly and expanded. This feeds still more excitement for more data. The snowball gets larger and increasingly rolls down the hill faster. Additionally, executives can see tangible, early success and feels comfortable funding the activities or expanding funding.</p>
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<p class="indent">Are you ready to change the way you manage your enterprise data?</p>
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</section>
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</section>
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</body>
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