In deze presentatie leest u over de volgende onderwerpen:
• Introduction: “All the Data”
• What is iKnow?
• iKnow and DeepSee
• Added value
• Feature overview
• Demo
4. What is “All the Data”?
Why were you hired?
• Job interview
• Years experience
• Relevant references
• Test scores
• All of the above
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5. What is “All the Data”?
What makes your insurance claim successful?
• The amount of money claimed
• The premium you pay each month
• The rating of your insurer
• What you paid your lawyer for filing it
• The claim itself
• All of the above
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6. What is “All the Data”?
• Decisions based on structured data:
• “Buy any book categorized “fiction” in this
month’s best-selling top 10, costing less than
20$”
• Decisions based on all the data:
• “Buy the book categorized “fiction” in this
month’s best-selling top 10, costing less than
20$, that is most different from the books I
already own.”
7. What is “All the Data”?
• Business decisions are based on “All the Data”
• Ignoring or neglecting parts of what you know is
not an option
• Most of today’s software stores “All the Data”
• A breakthrough application uses “All the Data”
8. Competing on Unstructured Data
What today’s Business Intelligence is based on
lack of useful insight
What today’s Business Decisions are based on
Structured
Data
Unstructured
Data
9. What Analysts are saying...
• Gartner BI Summit, April 2 – 4
• New in 2012: “Why big data and unstructured content
require special handling”
• Gartner Magic Quadrant for BI: Trends
• “Data Discovery momentum continues to accelerate”
• “An avalanche of new use cases and content types”
• Forrester: “Faceted search” is on the rise
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10. About search-based BI
• Search helps you find what you know:
• All service requests by customer X for period Y
containing the word “outlook”
• Content Insight will tell you what you don’t
know yet:
• Which were the common problems for all service
requests by customer X in period Y?
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12. What is iKnow?
• Generic text analysis technology
• Domain-independent
• Multi-purpose and multi-lingual
• Built into the core of Caché
• Enables applications to do something with text
13. What is iKnow?
• Core functionality:
• Identifies meaningful word groups (“entities”) in
sentences based on semantics
iKnow and DeepSee deliver Active Analytics
iKnow and DeepSee deliver Active Analytics
to your breakthrough applications
to your breakthrough applications
• Entities and their context are the basis of all
further analysis, such as:
• Queries within or across bodies of text
• Relevance calculations & summarization
• Matching against existing knowledge
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14. What iKnow isn’t
• iKnow is not search
• iKnow is not an application
• iKnow is not content management
• iKnow is not a medical coding tool
• iKnow is not a solution on its own
15. iKnow Use Cases
Content Creation
Content Linking
Content Consumption
Content Insight
Note: these are use cases, not features or functions
16. Content Insight
• Combines text with its structured
context to generate a broader
understanding of 100% of your data
• Provides both structured and unstructured outputs
• ... based on both structured an unstructured inputs
• Implemented through integration with DeepSee
18. iKnow in the InterSystems Platform
Advanced
Analysis of
100% of your
Data
Automating
labour-intensive
Business
Processes
Smarter end-user
Applications
20. What is DeepSee?
• DeepSee delivers Active Analytics, enhancing
transactional applications with embedded,
real-time Business Intelligence capabilities
• Key Components:
• Architect:
Define data model
• Analyzer:
Explore and display data
• User Portal: Create dashboards, extend apps
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21. iKnow in DeepSee
• What people like about DeepSee:
•
•
•
•
Performance
Ability to handle complex data
Ease of use
Thin client
Transparently embeds
BI in your application
22. iKnow in DeepSee
• Focus of iKnow integration:
•
•
•
•
Performance
Ability to handle complex data
Ease of use
Thin client
Transparently embeds
text analysis in your BI
26. Added Value
• Support structured data findings with proof
from the unstructured context
• Explain structured data findings with
summaries of unstructured context
• Extend structured data findings with
unstructured data findings
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27. Supporting Structured Data Findings
• Structured data does not necessarily mean it’s
exact science
• Manual input is vulnerable to human error
• Textual context can be mined for confirmation
• Examples
• Customer service: text-based category detection
• Healthcare: code / diagnosis verification
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28. Explaining Structured Data Findings
• Richness of natural language adds much detail
and context to measured facts
• Complement figures with their most relevant context
using summaries and semantics
• Examples
• Customer service: show dominant terms and trends
for a particular customer and time period
• Healthcare: read only the most typical and breaking
patient episodes for a given time period
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29. Extending Structured Data Findings
• Add new information not captured previously
in structured properties and dimensions
• True text analysis generates new insights
• Examples
• Customer service: prioritize and act based on mood
detection and information scoring
• Healthcare: populate empty or inexistent EHR fields
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32. Conclusion
• The combination of iKnow and DeepSee
enables complete, seamless and transparent
content insight
• Complete: unlocks 100% of your data
• Seamless: no separate tools or training required
• Transparent: adheres to strict APIs and default MDX
33. Conclusion
• The main BI question:
“Which figures and diagrams do I need to get an insight
into my business performance?”
• ... now gets an appendix:
“And what textual content can I use to support, explain
or extend this insight?”