Presented To: Madam Nadia Gul Presented By: Bi Bi Mariam.

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Presentation transcript:

Presented To: Madam Nadia Gul Presented By: Bi Bi Mariam

Data are any facts, numbers, or text that can be processed by a computer. Today, organizations are accumulating vast and growing amounts of data in different formats and different databases.

In computing, a data warehouse or enterprise data warehouse (DW, DWH, or EDW) is a database used for reporting and data analysis.

The Knowledge Discovery in Databases (KDD) process is commonly defined with the stages: Selection Pre-processing Transformation Data Mining Interpretation/Evaluation We will discuss now “Data Mining”

 Data mining (the analysis step of the "Knowledge Discovery in Databases" process or KDD), an interdisciplinary subfield of computer science,is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems.

The manual extraction of patterns from data has occurred for centuries. Bayes' theorem (1700s) Regression analysis (1800s) Neural networks, cluster analysis, genetic algorithms (1950s) Decision trees (1960s) Support vector machines (1990s)

Data mining involves six common classes of tasks: Anomaly detection Association rule learning Clustering Classification Regression Summarization

Data mining consists of five major elements: 1. Extract, transform, and load transaction data onto the data warehouse system. 2. Store and manage the data in a multidimensional database system. 3. Provide data access to business analysts and information technology professionals. 4. Analyze the data by application software. 5. Present the data in a useful format, such as a graph or table.

There are two critical technological drivers: 1. Size of the database 2. Query complexity

Data mining is used in the following fields mentioned below: Games Games Business Business Science and engineering Science and engineering Human rights Human rights Medical data mining Medical data mining Visual data mining Visual data mining Music data mining Music data mining

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