KNOWLEDGE DISCOVERY & DATA MINING Abhishek M. Mehta ROLL NO:24.

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Presentation transcript:

KNOWLEDGE DISCOVERY & DATA MINING Abhishek M. Mehta ROLL NO:24

TOPICS Why we required data mining? What is DATA MINING? Standards Of Data Mining Methods Of Data Mining What is KNOWLEDGE DISCOVERY? Process of KNOWLEDGE DISCOVERY Input Data For Knowledge Discovery Output Format For Discovered Knowledge

3 Requirement Of Data Mining Wal-Mart reported to have 24 Tera-byte DB AT&T handles billions of calls per day – data cannot be stored. Mobil Oil : 100 TB of Oil Exploration Data NASA: EOS –generates 50GB /hr Remotely Sensed Image Data

What is DATA MINING? Data mining is the process of analyzing data from different perspectives and summarizing it into useful information.

Standards Of Data Mining 1999 European Cross Industry Standard Process for Data Mining (CRISP-DM 1.0)Cross Industry Standard Process for Data Mining 2004 Java Data Mining standard (JDM 1.0).Java Data Mining

Methods of Data Mining Association rule learning Cluster analysis Structured data analysis (statistics) Java Data Mining Data analysis Predictive analytics Knowledge discovery

What is Knowledge discovery? The non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data non-trivial process Valid novel useful understandable

8 ____ __ __ Transformed Data Patterns and Rules Target Data Raw Dat a Knowledge Data Mining Transformation Interpretation & Evaluation Selection & Cleaning Integration Understanding Knowledge Discovery Process DATA Ware house Knowledge

Input Format of Knowledge Discovery Databases – Relational data – Database – Document warehouse – Data warehouse Software Mining Text Graphs Sequences Web

Output Format for Discovered knowledge Data model Metadata Metamodels Knowledge representation Knowledge tags Business rule Knowledge Discovery Metamodel(KDM) Business Process Modeling Notation (BPMN) Intermediate representation Resource Description Framework(RDF) Software metrics

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