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Modern Knowledge
Management
Agnes Molnar
Enterprise Search Consultant, Founder, MVP
Search Explained
Introduction – Agnes Molnar
• 8 years MVP (SharePoint, Office 365)
• Enterprise Search, Information Architecture
• Enterprise Search Consultant, Founder
• Worldwide Consultancy, Guidance, Trainings,
Workshops
• Web: http://SearchExplained.com
• Yammer: http://yammer.com/SearchExplained
• Community: http://ITUnity.com
• Twitter: @molnaragnes
• E-mail: agnes.molnar@SearchExplained.com
Agenda
• Information Overload Challenges
• Data vs. Information vs. Knowledge
• Enterprise Search
• Delve
• Office Graph
• Modern Knowledge Management
Search is Easy!?
Find is the REAL Challenge!
The Paradox of Content
Less Content – Less Value
More Content – More Garbage
Information Overload
The average person
receives 63,000 words
of new information
every day.
Average length of a
novel: 64.531 words
Social Overload
• Emails
• SharePoint
• Yammer
• LinkedIn
• Facebook
• Twitter
• …
Data vs. Information vs. Knowledge
• Data: Facts and figures of the World. Data is
not organized.
• Information: Contextualized, categorized,
calculated and organized data. Has a
purpose.
• Knowledge: Understanding, experience,
insight, intuition and information put into
context.
Information Architecture
The art and science of organizing and labeling
the CONTENT
(documents, web sites, blog posts, database entries, etc.)
to support findability and usability
Metadata Taxonomy Content Types
Sites Lists
Document
Libraries
Folders Document Sets Workflows
Content
Organizer
Rules
User Profiles Audiences
…
Information Architecture
Knowledge Management
The process
of capturing, developing,
sharing, and effectively using
organizational knowledge
Knowledge Management
People Processes Technology Culture
Structure Community
Intellectual
Capital
Knowledge Management
Codification Personalization Rewards Storytelling
Cross-project
learning
After action
reviews
Knowledge
Mapping
Expert
directories
Best Practice
transfer
Competence
management
Knowledge
repositories
Collaborative
technologies
Knowledge
brokers
Social software
Inter-project
knowledge
transfer
Search
Connects people
to the information
they need to get their jobs
done
Findability vs. Search
Search vs. Discovery
Delve:
to carry on intensive research for data or information;
investigate
Office Graph
An Introduction
Manager
Direct report
Works with
Shared with me
Viewed by me
Trending around me
Presented to me
Liked by me
Manager
Direct report
Works with
Shared with me
Viewed by me
Trending around me
Presented to me
Liked by me
Manager
Direct report
Works with
Shared with me
Viewed by me
Trending around me
Presented to me
Liked by me
Works with
Modified by
Jenny Gottfried
Trending around
Jenny Gottfried
Modified by
Jenny Gottfried
Liked by
Jim Geist
Emailed to me
Emailed to me
Works with
Modified by
Jim Geist
Modified by
Alan Brewer
Commented on
Commented on
Trending around
Nancy Anderson
Search Social
Enterprise
Intelligence
Big Data
Knowledge Management – Work
Like a Network
Knowledge = Users + Content +
Context
Content
UsersContext
Thank You!
Web: http://SearchExplained.com
Yammer: http://yammer.com/SearchExplained
Twitter: @molnaragnes / @SearchExplained
E-mail: agnes.molnar@SearchExplained.com
Ne zaboravite ispuniti upitnike.
Čekaju vas vrijedne nagrade!

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Modern Knowledge Management

Notas do Editor

  1. Display Templates Query Builder Result Sources Query Rules
  2. “The Average Person Today Processes More Data in a Single Day Than a Person in the 1500’s Did In an Entire Lifetime.”
  3. Mitchell Kapor: the founder of Lotus Development Corporation, the first chair of the Mozilla Foundation. Robby Walker Average novel: 64.500 words Amazon Text Stats Distracting, unmanageable
  4. KM is about…
  5. KM Tools Codification - collecting and storing codified knowledge in previously designed electronic databases to make it accessible to the organization Personalization - encouraging individuals to share their knowledge directly
  6. Proactive “Passive”
  7. Agnes Search metaphor broken and outdated Transition to Dan Maybe that’s not what we should be focused on… setup for findability
  8. Dan
  9. Agnes One way to think about Office Graph & Delve is as the mashup of 6 billion EDGES (raltionships)
  10. Identifying them is critical – but not easy at all!!!