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Data Mining: Key definitions

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DataminingTools Inc
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Data Mining: Key definitions

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Data miningand key definitions
What is Data Mining? Data mining is a result of the natural evolution of information technology. OLAP and OLTP are applications of data mining.
OLAP On-line transaction processing (OLTP), is an efficient method , where a query is viewed as a read-only transaction, have contributed substantially to the evolution and wide acceptance of relational technology as a major tool for efficient storage, retrieval, and management of large amounts of data
OLTP Data warehouse technology includes data cleaning, data integration, and on-line analytical processing (OLAP), that is, analysis techniques with functionalities such as summarization, consolidation, and aggregation as well as the ability to view information from different angles.
What Is Data Mining? Collect Data Remove noise Mine and get the portion of interest Analyze the data Get the required information Data Mining = Get Information from data
Components of Data mining System Data ware house server Information repository User Interface Data mining Engine Pattern Evolution Knowledge Base
What is a Data Ware House? A data ware-house is a repository of information collected from multiple sources, stored under a unified schema, and that usually resides at a single site.
Advanced Data and Information Systems A Transactional database consists of a file where each record represents a transaction. Object-relational databases are constructed based on an object-relational data model A Temporal database typically stores relational data that include time-related attributes.
Advanced Data and Information Systems cont.. Spatial databases contain spatial-related information. Examples include geographic (map) databases. Text databases are databases that contain word descriptions for objects A Heterogeneous database consists of a set of interconnected, autonomous component databases.
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Data Mining: Key definitions

  • 1. Data miningand key definitions
  • 2. What is Data Mining? Data mining is a result of the natural evolution of information technology. OLAP and OLTP are applications of data mining.
  • 3. OLAP On-line transaction processing (OLTP), is an efficient method , where a query is viewed as a read-only transaction, have contributed substantially to the evolution and wide acceptance of relational technology as a major tool for efficient storage, retrieval, and management of large amounts of data
  • 4. OLTP Data warehouse technology includes data cleaning, data integration, and on-line analytical processing (OLAP), that is, analysis techniques with functionalities such as summarization, consolidation, and aggregation as well as the ability to view information from different angles.
  • 5. What Is Data Mining? Collect Data Remove noise Mine and get the portion of interest Analyze the data Get the required information Data Mining = Get Information from data
  • 6. Components of Data mining System Data ware house server Information repository User Interface Data mining Engine Pattern Evolution Knowledge Base
  • 7. What is a Data Ware House? A data ware-house is a repository of information collected from multiple sources, stored under a unified schema, and that usually resides at a single site.
  • 8. Advanced Data and Information Systems A Transactional database consists of a file where each record represents a transaction. Object-relational databases are constructed based on an object-relational data model A Temporal database typically stores relational data that include time-related attributes.
  • 9. Advanced Data and Information Systems cont.. Spatial databases contain spatial-related information. Examples include geographic (map) databases. Text databases are databases that contain word descriptions for objects A Heterogeneous database consists of a set of interconnected, autonomous component databases.
  • 10. Visit more self help tutorials Pick a tutorial of your choice and browse through it at your own pace. The tutorials section is free, self-guiding and will not involve any additional support. Visit us at www.dataminingtools.net