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List the advantages and limitations of data mining to support an Information system? Also, discuss the importance of business intelligence. Explain how “Big Data Technology” is affecting data mining.

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Advantages of Data Mining
Marketing / Retail
Data mining helps marketing companies build models based on historical data to predict who will respond to the new marketing campaigns such as direct mail,
online marketing campaign…etc. Through the results, marketers will have an appropriate approach to selling profitable products to targeted customers.
Data mining brings a lot of benefits to retail companies in the same way as marketing. Through market basket analysis, a store can have an appropriate production
arrangement in a way that customers can buy frequent buying products together with pleasant. In addition, it also helps the retail companies offer certain discounts
for particular products that will attract more customers.
Finance / Banking
Data mining gives financial institutions information about loan information and credit reporting. By building a model from historical customer’s data, the bank,
and financial institution can determine good and bad loans. In addition, data mining helps banks detect fraudulent credit card transactions to protect credit card’s
By applying data mining in operational engineering data, manufacturers can detect faulty equipment and determine optimal control parameters. For example,
semiconductor manufacturers have a challenge that even the conditions of manufacturing environments at different wafer production plants are similar, the quality
of wafer are a lot the same and some for unknown reasons even has defects. Data mining has been applying to determine the ranges of control parameters that lead
to the production of the golden wafer. Then those optimal control parameters are used to manufacture wafers with desired quality.
Data mining helps government agency by digging and analyzing records of the financial transaction to build patterns that can detect money laundering or criminal
Limitation of data mining
Privacy Issues
The concerns about the personal privacy have been increasing enormously recently especially when the internet is booming with social networks, e-commerce,
forums, blogs…. Because of privacy issues, people are afraid of their personal information is collected and used in an unethical way that potentially causing them a
lot of troubles. Businesses collect information about their customers in many ways for understanding their purchasing behaviors trends. However businesses don’t
last forever, some days they may be acquired by other or gone. At this time, the personal information they own probably is sold to other or leak.
Security issues
Security is a big issue. Businesses own information about their employees and customers including social security number, birthday, payroll and etc. However how
properly this information is taken care is still in questions. There have been a lot of cases that hackers accessed and stole big data of customers from the big
corporation such as Ford Motor Credit Company, Sony… with so much personal and financial information available, the credit card stolen and identity theft
become a big problem.
Misuse of information/inaccurate information
Information is collected through data mining intended for the ethical purposes can be misused. This information may be exploited by unethical people or
businesses to take benefits of vulnerable people or discriminate against a group of people.
In addition, data mining technique is not perfectly accurate. Therefore, if inaccurate information is used for decision-making, it will cause serious consequence.
Business Intelligence
The term business intelligence (BI) typically refers to a set of business processes for collecting and analyzing business information. This includes the technology
used in these processes, and the information obtained from these processes.
The information economy puts a premium on high quality actionable information — exactly what Business Intelligence (BI) tools like data warehousing, data
mining, and OLAP can provide to the business. A close look at the different organisational functions suggests that BI can play a crucial role in almost every
function. It can give new and often surprising insights about customer behavior; thereby helping the businesses meeting their ever-changing needs and desires. On
the supply side, BI can help businesses to identify their best vendors and determine what separates them from not so good vendors. It can give businesses better
understanding of inventory and its movement and also help improve production and storefront operations through better category management. Through a host of
analyses and reports, BI can also improve internal organisational support functions like finance and human resource management of any business.
Business Intelligence is applicable to all types of businesses; however, the magnitude of gains may vary. Here we will discuss in detail how BI can improve the key
functional areas and thereby the overall productivity of the business.
Big Data Technology
Big Data and data mining are completely different concepts. However, both concepts involve the use of large data sets to handle the collection or reporting of data
that helps businesses or clients make better decisions. However, the two concepts are used in two different elements of this operation.
The term Big Data can be defined simply as large data sets that outgrow simple databases and data handling architectures. For example, data that cannot be easily
handled in Excel spreadsheets may be referred to as Big Data.

Data mining relates to the process of going through large sets of data to identify relevant or pertinent information. Businesses often collect large data sets that may
be automatically collected. However, decision makers need access to smaller, more specific pieces of data and use data mining to identify specific data that may
help their businesses make better leadership and management decisions.

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