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2. WHAT DO YOU
UNDERSTAND BY DATA
MINING?
One of the key elements of database administration is data mining. it is a procedure for selecting the
necessary data from a large collection of data in order to obtain accurate information for the
organisation. the ability of data mining to recognise links and patterns in massive amounts of data from
numerous sources is one of its key advantages. it comprises the procedure of evaluating and analysing
a sizable batch of unstructured data in order to find patterns and extract data.
3. COMPONENTS OF
DATA MINING
There are various components of data mining
that helps in its smoother work flow of the
database management system :
Data mining engine
User Interface
Data warehouse server
Knowledge base
Module for pattern evaluation
4. STEPS IN DATA
MINING
Establishing the process
Preparation of data
Exploring data
Model building
Exploring and evaluating
Updating and deploying
5. DATA MINING
TECHNIQUES
Algorithms and other approaches are used in data mining to
transform massive data sets into useable output.
Association rules
Classification
Clustering
Decision trees
Nearest Neighbors
Neural networks
Predictive analysis
6. APPLICATIONS OF DATA MINING
Sales
Marketing
Manufacturing
Fraud Detection
Human resources
Customer satisfaction
7. USES OF DATA MINING
There are various uses of data mining. List of it is below :-
Basket Analysis
Sales forecasting
Database marketing
Inventory planning
Customer loyalty
8. BENEFITS OF DATA MINING
• It aids businesses in making wise selections.
• It enables data scientists to swiftly launch automated behavioral and trend
predictions and find covert pattern.
• It aids businesses in obtaining accurate information.
• Compared to other data applications, it is a productive and affordable solution.
• Businesses can adapt their operations and production in a lucrative way.
• It aids in identifying fraud and credit risks.
9. DISADVANTAGES OF DATA MINING
• Data mining is challenging and intricate, so thorough instruction in the use of
numerous technologies is necessary.
The method is challenging since mining requires a sizable database.
Data mining is not always accurate and, in some circumstances, might have
negative effects.
It is certain that each tool has a unique algorithm, choosing the best one for a
certain firm is a difficult issue.