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OLAP, OLTP and Data Mining
TitleData WarehouseDW DiagramOLTPOLAPData MiningData Mining goalData Mining Elements Data Mining ApplicationDW VS Data MiningThanks
Data Warehouses Repository is a key data warehouse
component Data warehouses provide access to data for
complex analysis, knowledge discovery, and decision making.
Data warehousing more generally as a collection of decision support technologies, aimed at enabling the knowledge worker (executive, manager, analyst) to make better and faster decisions.
Extract, Transform and Load Pulling data out of the source system and
placing it into a data warehouse Cleaning Filtering Splitting a column into multiple columns Joining together. loading the data into a data warehouse
On-line Transaction Processing Use in Traditional databases Includes insertions, updates, and
deletions, while also supporting information query requirements
On-line Analytical Processing To describe the analysis of complex
data from the data warehouse ROLAP (relational OLAP) and
MOLAP (multidimensional OLAP) functions
Knowledge Discovery ProcessThe knowledge discovery process comprises
six phases Data selection, Data cleansing, Enrichment, Data transformation or encoding,
Data mining, Reporting and display of the discovered
information.
Data Mining Data Mining as a Part of the
Knowledge Discovery Process Used for knowledge discovery, the
process of searching data for the new knowledge.
Data mining consists of five major elements:
Extract, transform, and load transaction data onto the data warehouse system.
Store and manage the data in a multidimensional database system.
Provide data access to business analysts and information technology professionals.
Analyse the data by application software. Present the data in a useful format, such as a
graph or table.
Goal of Data Mining
Prediction Identification Classification(combinations of parameters) Optimization(Goal of data mining may be
to optimize the use of limited resources such as time, space, money, or materials and to maximize output variables such as sales or profits under a given set of constraints)
Applications of Data Mining
Marketing Finance Manufacturing Health Care Many people only need read-access to data, but still
need a very rapid access to a larger volume of data than can conveniently be downloaded to the desktop. Data comes from multiple databases
Such types of functionality provide:- Data warehousing, on-line analytical processing
(OLAP), and data mining
DW VS DM Data warehousing can be seen as a
process that requires a variety of activities to precede it;
Data mining may be thought as an activity that draws knowledge from an existing data warehouse.
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