Data Mining: Data mining and 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. OLAPOn-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. OLTPData 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 DataRemove noiseMine and get the portion of interestAnalyze the dataGet the required information Data Mining = Get Information from data
- 6. Components of Data mining SystemData ware house serverInformation repositoryUser InterfaceData mining EnginePattern EvolutionKnowledge 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 SystemsA Transactional database consists of a file where each record represents a transaction.Object-relational databases are constructed based on an object-relational data modelA 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 objectsA Heterogeneous database consists of a set of interconnected, autonomous component databases.
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