Data Mining Technique for Business

Running Head: DATA MINING TECHNIQUE FOR BUSINESS
0
Data Mining Technique for Business
Report
Student name

Data Mining Technique for Business 1
Table of Contents
Introduction......................................................................................................................................2
Data mining technique for industry business...................................................................................3
Data mining tools.........................................................................................................................3
Data implementations and preparation........................................................................................4
Applications of the business analytics and Data Mining techniques...............................................4
Challenges......................................................................................................................................12
Conclusion.....................................................................................................................................12
References......................................................................................................................................14

Data Mining Technique for Business 2
Introduction
Data mining techniques are helpful in reporting of different business analytics, which are
uses for decision-making. Business processes are having different types of decision-making
conditions and it is a tough task to take decisions based on data, which is calculated based on
different information of related things. Business Intelligent is outside the scope of data. There are
basic things, which are used for business processes. It transforms the data into actionable
information. That information is used for calculations. It helps in optimizing organizations
strategic. It is also used for tactical business decisions using the applications, infrastructure and
tools. It is the best practices that support access to the effective facts of an organization using
data mining techniques.
This report will review the applications of business intelligence as well as data mining in
different industry domain in contexts of decision-making. Today’s business is completely based
on the data analytics and tools, which are providing the information about decision-making.
There are so many techniques, which are providing reporting from the collected data from
different sources.
There are so many types of business intelligence analytics, which is providing different
advantages to an organization, such as predictive analytics, business-intelligence data mining,
text mining, text analytics, customer analytics and sentiment analysis. Data mining is a process,
which applies to large data sets, which is integrate from the different sources such as sensors,
social media, mobile phones, websites, online transitions and databases. The information getting
from the reports of data mining is providing opportunities to the organization in their real
business.
This report will explain about the data mining technique’s role in the business
intelligence. This report will mainly focus on three areas, which are customer relationship
management, banking industry and education industry in next parts. Data mining is providing
competitive advantage to the organization from their own databases, which is stored in their
system. In this report, decision management, information integration, content analytics, data

Data Mining Technique for Business 3
warehousing, business intelligence, stream computing, planning, forecasting, governance,
discovery and exploration will discuss in details in later sections.
Data mining technique for industry business
Data mining is having different techniques for managing data, which is stored in the data
warehouses. It is a process in which data warehouses are used for data and these techniques are
used for reporting. Reports are provides information for decision-making. Conceptually, data
mining is a process, which is process data and it is find different patterns. That information is
helpful for decision-making or judge. Big data make it more prevalent. It is using from many
years but it is more beneficial for the business as well as organizations to decision-making for
their investment in future time. Big data is beneficial for more extensive data mining techniques.
It based on the size of information because of nature and content, which is more varied and
extensive. Dealing with lots of data is not enough but it requires more attributes in that particular
data (Cuzzocrea, 2014).
This is an iterative process in which data analysis, discovery, and model building is used
for extracting more information from data sets. It is helpful for producing results as well as
understands how to relate, map, associate, and cluster all the data. It is also providing formats
and source of data to identifying and mapping that information for discovers different elements
(Gandomi & Haider, 2015).
Data mining tools
SQL databases are following the strict structures but it is useful for better results as well
as reduces complexity for mining. Structuring matters a lot for fast accessing of data and it is
reporting processing. Document databases are enforcing structure, which is easier to process
( Wilson, 2017).
Data mining techniques are used in the data mining projects for helping different areas,
such as education, banking, healthcare, and customer relationship management (Baepler &
Murdoch, 2010).
These are the techniques, which are used by the data mining: