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Data Mining Group Members Alisha Korpal Nivia Jain Sharuti Jain
Data Mining ? ,[object Object],[object Object],[object Object],[object Object]
Data vs. Information
[object Object],[object Object],[object Object]
Data Mining ,[object Object],[object Object],[object Object]
Data Mining Process ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Mining Process
Defining the Problem ,[object Object],[object Object]
Contd… ,[object Object],[object Object],[object Object]
Preparing Data
Exploring Data   ,[object Object]
Models ,[object Object],[object Object],[object Object]
Evolution of Data Mining ,[object Object],[object Object],[object Object],[object Object]
Prospective, proactive information delivery Advanced algorithms, multiprocessor computers, massive databases "What’s likely to happen to Boston unit sales next month? Why?" Data Mining (Emerging Today) Retrospective, dynamic data delivery at multiple levels On-line analytic processing (OLAP), multidimensional databases, data warehouses "What were unit sales in New England last March? Drill down to Boston." Data Warehousing & Decision Support (1990s) Retrospective, dynamic data delivery at record level Relational databases (RDBMS), Structured Query Language (SQL), ODBC "What were unit sales in New England last March?" Data Access (1980s) Retrospective, static data delivery Computers, tapes, disks "What was my total revenue in the last five years?" Data Collection (1960s) Characteristics Enabling Technologies Business Question Evolutionary Step
Data mining Vs OLAP ,[object Object],[object Object]
Scope of Data Mining ,[object Object],[object Object]
Applications ,[object Object],[object Object],[object Object],[object Object]
Applications ,[object Object],[object Object],[object Object],[object Object]
Applications ,[object Object],[object Object],[object Object]
Applications ,[object Object],[object Object],[object Object]
References:   ,[object Object],[object Object]
References: ,[object Object],[object Object],[object Object]
Conclusion
Result of Data Mining ,[object Object],[object Object],[object Object],[object Object]
Data Mining is not ,[object Object],[object Object],[object Object],[object Object]
Necessity is the  mother of invention
Thank you

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Data mining

  • 1. Data Mining Group Members Alisha Korpal Nivia Jain Sharuti Jain
  • 2.
  • 4.
  • 5.
  • 6.
  • 8.
  • 9.
  • 11.
  • 12.
  • 13.
  • 14. Prospective, proactive information delivery Advanced algorithms, multiprocessor computers, massive databases "What’s likely to happen to Boston unit sales next month? Why?" Data Mining (Emerging Today) Retrospective, dynamic data delivery at multiple levels On-line analytic processing (OLAP), multidimensional databases, data warehouses "What were unit sales in New England last March? Drill down to Boston." Data Warehousing & Decision Support (1990s) Retrospective, dynamic data delivery at record level Relational databases (RDBMS), Structured Query Language (SQL), ODBC "What were unit sales in New England last March?" Data Access (1980s) Retrospective, static data delivery Computers, tapes, disks "What was my total revenue in the last five years?" Data Collection (1960s) Characteristics Enabling Technologies Business Question Evolutionary Step
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 24.
  • 25.
  • 26. Necessity is the mother of invention