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Data Mining:
Introduction,
Types and
Elements
Contents:
Introduction
Types of Data Mining
Elements of Data Mining
Conclusion
When we extract
beneficial
information from
the huge volume of
data, this process is
called as Data
Mining.
Introduction
Types of Data Mining
Descriptive Data Mining Analysis
Descriptive data mining analysis
involves the process if converting
provided data into useful information.
Descriptive Data mining is further
classified into summarization analysis,
sequence discovery analysis, association
rules analysis and clustering analysis.
Predictive Data Mining Analysis
As the name manifest, predictive data
mining is the analysis of all the data that
can be helpful to predict the future
outcomes.It is further classified into
regression analysis, prediction analysis,
time-serious analysis and classification
analysis.
Elements of Data Mining:
Extraction, Transformation and Loading
Data mining extracts, transform and
loads the data towards data warehouse
system.
Storing and Managing data
It stores and manages the extracted
data in a multidimensional data system.
Data Access
It provides data access to information
technology professionals and data
analysts so to work further.
Data Analyzing
It analyses the data through the
application software and present data
into useful structure.
Conclusion
Data mining is the process which helps
the businesses to analyze consumer's
behaviour and their insights. It also
enhances the quality of decisions and
improves security. It is considered as
one of the most effective ways to
improve forecasting and planning.
Contact Us
+61 280 113 341
support@assignmentachievers.com
www.assignmentachievers.com
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Assignments?
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Introduction to Data Mining.pptx

  • 2. Contents: Introduction Types of Data Mining Elements of Data Mining Conclusion
  • 3. When we extract beneficial information from the huge volume of data, this process is called as Data Mining. Introduction
  • 4. Types of Data Mining Descriptive Data Mining Analysis Descriptive data mining analysis involves the process if converting provided data into useful information. Descriptive Data mining is further classified into summarization analysis, sequence discovery analysis, association rules analysis and clustering analysis.
  • 5. Predictive Data Mining Analysis As the name manifest, predictive data mining is the analysis of all the data that can be helpful to predict the future outcomes.It is further classified into regression analysis, prediction analysis, time-serious analysis and classification analysis.
  • 6. Elements of Data Mining: Extraction, Transformation and Loading Data mining extracts, transform and loads the data towards data warehouse system. Storing and Managing data It stores and manages the extracted data in a multidimensional data system.
  • 7. Data Access It provides data access to information technology professionals and data analysts so to work further. Data Analyzing It analyses the data through the application software and present data into useful structure.
  • 8. Conclusion Data mining is the process which helps the businesses to analyze consumer's behaviour and their insights. It also enhances the quality of decisions and improves security. It is considered as one of the most effective ways to improve forecasting and planning.
  • 9. Contact Us +61 280 113 341 support@assignmentachievers.com www.assignmentachievers.com Need assistance with your Data Mining Assignments? We are here to assist you!!