DWH-Ahsan Abdullah 1 Data Warehousing Lecture-29 Brief Intro. to Data Mining Virtual University of Pakistan Ahsan Abdullah Assoc. Prof. & Head Center.

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DWH-Ahsan Abdullah 1 Data Warehousing Lecture-29 Brief Intro. to Data Mining Virtual University of Pakistan Ahsan Abdullah Assoc. Prof. & Head Center for Agro-Informatics Research National University of Computers & Emerging Sciences, Islamabad

DWH-Ahsan Abdullah 2 What is Data Mining?: Non technical view “There are things that we know that we know… there are things that we know that we don’t know… there are things that we don’t know we don’t know.” Donald Rumsfield US Secretary of Defence

DWH-Ahsan Abdullah 3 What is Data Mining?: Slightly formal

DWH-Ahsan Abdullah 4 What is Data Mining?: Formal view Data mining digs out valuable non-trivial information from large multidimensional apparently unrelated data bases(sets).

DWH-Ahsan Abdullah 5 Why Data Mining? Huge volume

DWH-Ahsan Abdullah 6 Claude Shannon's info. theory More volume means less information

DWH-Ahsan Abdullah 7 Volume of Data Value vs. Volume Value of Data Decision (Y/N) Decision Support KnowledgeInformation Indexed Data Raw Data

DWH-Ahsan Abdullah 8 Why Data Mining?: Supply & Demand

DWH-Ahsan Abdullah 9

10 Data Mining is HOT!  10 Hottest Jobs of year 2025 Time Magazine, 22 May, 2000  10 emerging areas of technology MIT’s Magazine of Technology Review, Jan/Feb, 2001

DWH-Ahsan Abdullah 11 How Data Mining is different? Traditionally  Data Warehouses (Data-driven exploration): Knowledge-driven exploration Data Mining (Knowledge-driven exploration) Traditional Database (Transactions): Knowledge Discovery (KDD)

DWH-Ahsan Abdullah 12 Data Mining Vs Statistics

DWH-Ahsan Abdullah 13 Data Mining Vs. Statistics

DWH-Ahsan Abdullah 14 Knowledge extraction using statistics Q: What will be the stock increase when inflation is 6%? A: Model non-linear relationship using a line y = mx + c. Hence answer is 13%

DWH-Ahsan Abdullah 15 Failure of regression models Failure of regression models

DWH-Ahsan Abdullah 16 Data Mining is…  Decision Trees  Neural Networks  Rule Induction  Clustering  Genetic Algorithms If..... Then...

DWH-Ahsan Abdullah 17 Data Mining is NOT...  Data warehousing  Ad Hoc Query / Reporting  Online Analytical Processing (OLAP)  Data Visualization  Software Agents 

DWH-Ahsan Abdullah 18 Data Mining: Business Perspective  “knowledge” is worth knowing if it can be used to increase profit by lowering cost or it can be used to increase profit by raising revenue. Business questions  Profiling/Segmentation  Cross-Service  Employee retention: