Tutorial work Consider a census data set created jointly by local authorities, w

Question

Tutorial work Consider a census data set created jointly by local authorities, which contains more than thousand records and has the following variables: Variable Name Data Type Variable Description Record Number ID CRIM ME Crime rate in the region Average value of residential properties in the ratio Region longitude Region latitude Number of people in the region Average number of rooms per dwelling in the region Puplil-teacher ratio in the region Number of state schools in the region Number of independent schools in the region LOCK LOCY ratio RM ratio REGPT ratio interval interval REGIND Suggest two potential data mining tasks you may conduct with this data set, one for predictive modelling and the other for descriptive modelling. Briefly discuss what information/knowledge/patterns you would expect to find out from your data mining process. Any other meaningful data mining tasks? Search on the Internet for an article describing a case study of applying data mining in a business sector (such as retail, healthcare, medical diagnosis, education, banks, insurance, etc, etc...). Study the case study carefully and answer the following questions: What business problem was concerned and why? What data mining task(s) was (were) performed and why? What procedures/methodologies were followed in order to conduct the data mining exercise? What data mining algorithm(s) was (were) used and why? . The outcomes of the data mining process, and how they were used to support the business. Please attempt these questions before you attend the tutorial Page 2 of 2

Explanation / Answer

Data mining:
Data mining is a processing data that can helps in pattern identifying.
Data mining is more prevalent.
Generally big data is used for data mining techniques because the
size of information is big so that information is varied.
Data mining helps in business problem.
application og data mining:
1.massive collection of data
2.Highly using multiprocessor computers
3.data mining algorithms.
In data mining the data preprocessing consists of following
process:
1.selection
2.preparation
3.transformation
In oracle data mining helps in knowledge deployment.

predicting:
used in combination with the data mining techniques it will helps in
trends analyzing,classification,matching the pattern and their relation.
predictive modelling:
predictive model contains the create,testing and validate a model to
get a desired output.
descriptive model help a company to understand the clients,but output
is depends on the customer requirement.
so predictive model is preferable.

what business problems was concerned by data mining

1.DAta mining helps in missing data,noisy data.
2.High cost of buying and maintains the powerful
softwares and store hardware which can handle very big
amount of data.
3.helps in large complex data in to strcture format.

data mining tasks are:
1.clustering
2.summarization
3.classification
4.association
5. trend analysis

Data mining metholodigies are:

Understanding The business

Understanding the data

Preparation of data

Modelling the data

Data Evaluation

DataDeployment

k-means

Apriori

Support vector machines

EM

C4.5

PageRank

kNN

CART

AdaBoost

Naive Bayes

These helps in sloving the problem by step by step analysis

data mining support the business problem morethan data analysis.

data mining helps to take scope of methods and slove business problems
one step further.
decision making is able to participate in the process.
Understand the business objectives and support the business.

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