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Knowledge Graphs are Worthless, Knowledge Graph Use Cases are Priceless

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Knowledge Graphs are Worthless, Knowledge Graph Use Cases are Priceless

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At Knowledge Graph Forum 2022, Lulit Tesfaye and Sara Nash, Senior Consultant discuss the importance of establishing valuable and actionable use cases for knowledge graph efforts. The discussion draws on lessons learned from several knowledge graph development efforts to define how to diagnose a bad use case and outlined their impact on initiatives - including strained relationships with stakeholders, time spent reworking priorities, and team turnover. They also share guidance on how to navigate these scenarios and provide a checklist to assess a strong use case.

At Knowledge Graph Forum 2022, Lulit Tesfaye and Sara Nash, Senior Consultant discuss the importance of establishing valuable and actionable use cases for knowledge graph efforts. The discussion draws on lessons learned from several knowledge graph development efforts to define how to diagnose a bad use case and outlined their impact on initiatives - including strained relationships with stakeholders, time spent reworking priorities, and team turnover. They also share guidance on how to navigate these scenarios and provide a checklist to assess a strong use case.

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Knowledge Graphs are Worthless, Knowledge Graph Use Cases are Priceless

  1. 1. Knowledge Graphs are Worthless, Knowledge Graph Use Cases are Priceless Knowledge Graph Forum NYC September 29, 2022
  2. 2. Expertise in knowledge graph design, implementation, and scale. Enterprise Knowledge Lulit Tesfaye Partner and Division Director, Data and Information Management Sara Nash Senior Consultant
  3. 3. “Just convert this to RDF” “Let’s pilot a graph database” “Let’s start with everything in this one system” “We don’t have to know who is going to use it yet”
  4. 4. This leads to… “Just convert this to RDF” “Let’s pilot a graph database” “Let’s start with everything in this one system” “We don’t have to know who is going to use it yet” Strained Relationships with Stakeholders 360+ Hours Spent Reworking Priorities Team Turnover and Internal Frustration 50+ Hours Spent on Workarounds for Design & Validation
  5. 5. ENTERPRISE KNOWLEDGE Why Do Graph Efforts Fail? Many KG implementations fail because… The business does not understand the value and ROI There is no clear product vision Use case is not clearly defined or scoped to be achievable Source data and systems are not accessible The initiative is siloed from other enterprise initiatives
  6. 6. ENTERPRISE KNOWLEDGE What Use Cases Allow Us to Do Use cases drive successful knowledge graph implementation by… Providing a value statement that is easy to communicate Giving guidance to development teams on priorities Defining guardrails to scope successful increments of development Aligning different efforts on the team to a shared goal Laying a foundation for scale
  7. 7. An Effective Use Case Business Content/ Data Technical Use Case Scope Roles ● Persona development ● User stories Rules ● Triggers ● Interactions ● Sample inputs Resources ● Content ● Data ● Technical use case Requirements ● Functionality ● Outputs ● Questions/Sample queries Purpose ● Metrics/KPI ● Business value End User Lead working in risk management, Action identify the risks derived from an acquisition, Outcome I can generate the W report required by X regulator
  8. 8. Diagnosing a Bad Use Case
  9. 9. Diagnosing a Bad Use Case No End User Not Actionable It’s an Initiative Inability to Scale
  10. 10. Diagnosing a Bad Use Case: No End User Impact ● Too general ● Fail to account for different experiences of novice vs. expert users or those with otherwise different backgrounds or skill sets ● Lack of relevant application How to Navigate ● Work with stakeholders to understand end users ● Prioritize 1-2 user groups per use case ● Engage with representatives from user group to validate design and development efforts “I want to integrate data from 4 legacy systems to support advanced analytics, automated reporting and data lineage”
  11. 11. Impact ● Misalignment from stakeholders on the goals and capabilities of the graph ● At release, may not meet the needs of downstream systems ● Ontology design lacks direction How to Navigate ● Define triggers and expected outputs from the graph ● Use pseudo queries and questions to establish requirements ● Develop the graph with downstream application integration in mind “I want to integrate all domain data to serve as the hub for all research” Diagnosing a Bad Use Case: Not Actionable
  12. 12. Impact ● Too broad ● Not achievable in a short timeframe, risking showing no value for engagement ● Leads to confusion on internal teams on priorities How to Navigate ● Break the initiative down into achievable use cases, using personas and actions as drivers ● Develop a roadmap that communicates to stakeholders how increments feed into initiative ● Prioritize showing value quickly “I want to model all components of content management at the firm” Diagnosing a Bad Use Case: It’s an Initiative
  13. 13. Impact ● Have no long-term value ● Quickly become obsolete ● Lead to lost investment and frustration How to Navigate ● Develop a strategy and roadmap that captures future expansion ● Consider ongoing maintenance and governance needs “Let’s build this on static data” Diagnosing a Bad Use Case: Inability to Scale
  14. 14. ENTERPRISE KNOWLEDGE Approach to Designing a Strong Use Case Identify specific end users Address a foundational business problem Garner high participant interest Communicate specific outcomes Result in a “clickable” product Are not overly complex to implement Have the required resources readily available Provide a repeatable approach for subsequent implementations As a portfolio manager, I want to see the most recent fact sheet for a fund, so that I can quickly decide on an investment.
  15. 15. How Use Cases Drive Knowledge Graph Efforts ONTOLOGY ARCHITECTURE EXECUTIVE ALIGNMENT ● Collaborate with SMEs who represent personas to design and validate ● Leverage pseudo queries to define concept and relationship needs ● Prioritize areas of design by critical concepts for the use case ● Define integration needs with downstream systems ● Establish key users and access needs ● Determine and prioritize needs from source systems ● Provide value statement for graph efforts ● Drive achievable, visible progress that can be demoed to the business ● Translate technical efforts into tangible actions
  16. 16. ENTERPRISE KNOWLEDGE Landscape of Applications for Knowledge Graphs Entity Resolution Identification of Risks & Opportunities Data Governance and Quality Management 360 Views Intelligent Reporting and Insights Chatbots Recommendations Engine Case/Issue Routing Advanced Reporting & Decision-Making Content Personalization Expertise Locator Learning and Badging Auto-Tagging Semantic Search Reporting and Analytics Discovery, Standardization & Quality Control Content Management Navigation Search and Faceting Tagging Ontology and Knowledge Graph Basic Taxonomy Advanced Taxonomy Use Case Level Use Case Business Value Semantic Formalization & Expressivity Maintenance Development Cycle Strategy
  17. 17. ENTERPRISE KNOWLEDGE Any Questions? Thank you for listening. We are happy to take any questions at this time. Lulit Tesfaye ltesfaye@enterprise-knowledge.com www.linkedin.com/in/lulit-tesfaye/ Sara Nash snash@enterprise-knowledge.com www.linkedin.com/in/sara-g-nash/

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