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Critical Success Factors ,[object Object],[object Object],[object Object],[object Object]
Mechanisms: Consistent Critical Success Factors ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Critical Success Factors ,[object Object],[object Object],[object Object]
Critical Success Factors for M&A ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Critical Success Factors Strategy &  Leadership For a Coactive Policing Style Inputs Community Leadership & Accountability (Social & Political) Structure Service  Delivery Culture & Capacity Outputs Improved Public Outcomes
Critical Success Factors ( Inputs)   ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Strategy &  Leadership Raising the Game Raising the Game
Critical Success Factors ( Transforming #1)   ,[object Object],Structure ,[object Object],[object Object],[object Object],[object Object],Making a Difference
Critical Success Factors   (Transforming #2)   ,[object Object],Delivery ,[object Object],[object Object],[object Object],[object Object],[object Object],Making a Difference
Critical Success Factors (Outputs and Feedback Loop)   ,[object Object],Culture and Capacity Reinforcing Success ,[object Object],[object Object],[object Object],[object Object]
Knowledge Discovery Process of non trivial extraction of implicit, previously unknown and potentially useful information from large collections of data
So What Is Data Mining? •   In theory,  Data Mining  is a step in the knowledge discovery process. It is the extraction of implicit information from a large dataset. •  In practice, data mining and knowledge discovery are becoming synonyms.
What Can Be Discovered? What can be discovered depends upon the data mining task employed. • Descriptive DM tasks Describe general properties • Predictive DM tasks Infer on available data
What kind of information are we collecting? •  Business transactions •  Scientific data (biology, physics, etc.) •  Medical and personal data •  Surveillance video and pictures •  Satellite sensing •  Games
(Con’t) •  Digital media •  CAD and Software engineering •  Virtual worlds •  Text reports and memos •  The World Wide Web
Business Intelligence ,[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Business Intelligence
Business Intelligence Tools ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Business Intelligent Solutions •  BIS is a set of software products for: –  Visualizing information –  Data mining –  Query formulation –  E-commerce applications –  Integrating heterogeneous data (data warehouses, portals)
Data Warehousing   ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Warehousing Benefits ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Warehouse Components ,[object Object],[object Object],[object Object],[object Object]
Characteristics of Data Warehousing 1 .  Data organized by detailed subject with information relevant for decision support 2 .  Integrated data 3 .  Time - variant data 4 .  Non - volatile data
DW Suitability   ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Critical Success Factors

  • 1.
  • 2.
  • 3.
  • 4.
  • 5. Critical Success Factors Strategy & Leadership For a Coactive Policing Style Inputs Community Leadership & Accountability (Social & Political) Structure Service Delivery Culture & Capacity Outputs Improved Public Outcomes
  • 6.
  • 7.
  • 8.
  • 9.
  • 10. Knowledge Discovery Process of non trivial extraction of implicit, previously unknown and potentially useful information from large collections of data
  • 11. So What Is Data Mining? • In theory, Data Mining is a step in the knowledge discovery process. It is the extraction of implicit information from a large dataset. • In practice, data mining and knowledge discovery are becoming synonyms.
  • 12. What Can Be Discovered? What can be discovered depends upon the data mining task employed. • Descriptive DM tasks Describe general properties • Predictive DM tasks Infer on available data
  • 13. What kind of information are we collecting? • Business transactions • Scientific data (biology, physics, etc.) • Medical and personal data • Surveillance video and pictures • Satellite sensing • Games
  • 14. (Con’t) • Digital media • CAD and Software engineering • Virtual worlds • Text reports and memos • The World Wide Web
  • 15.
  • 16.
  • 17.
  • 18. Business Intelligent Solutions • BIS is a set of software products for: – Visualizing information – Data mining – Query formulation – E-commerce applications – Integrating heterogeneous data (data warehouses, portals)
  • 19.
  • 20.
  • 21.
  • 22.
  • 23. Characteristics of Data Warehousing 1 . Data organized by detailed subject with information relevant for decision support 2 . Integrated data 3 . Time - variant data 4 . Non - volatile data
  • 24.