Business Intelligence, Data Mining and Predictive Analysis

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Abstract
The present paper discusses about business intelligence, data analytics and the predictive
analysis. In the present times, the competition in the business environment is very high, which
makes it essential for the business organizations to obtain information about current nosiness
environment. The business intelligence refers to the process of obtaining information, which can
assist in the strategic business decisions. In the data mining, information is obtained through the
database of the company. There are various stages in the data mining such as generation,
aggregation, analysis and visualization of the information. Other than that, predictive analysis
refers to the forecasting of the future trends, based on the current events.
Keywords: business intelligence, data mining, generation, aggregation, analysis, visualization
and predictive analysis

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Introduction
In the present competitive times, it is important to gather information about the consumer
preferences and the changes in the marketplace to attain a competitive advantage over the
competitors. The business organization obtains the consumer insights and the knowledge of the
changes in the market, through various methods. The business intelligence is the information,
which assists in the strategic decision making of the organization. The business intelligence can
be stated as the data-driven decision making. It assists the business managers to take informed
decisions. However, the acquisition of critical and strategic information requires several steps. It
includes the generation, aggregation, analysis and visualization of the information. The data
mining encompasses all the activities in the generation and processing of business information.
However, business intelligence refers to the process in which the business leaders use this
information to make strategic decisions of the organization. Therefore, business intelligence is
not a technological term as it encompasses all the activities required to process the data and
support the data collection, sharing and reporting the information for the strategic decisions of
the organization (Hall, Frank, Holmes, Pfahringer, Reutemann & Witten, 2009).
There are several business intelligence tools, which allows the business decision makers to
generate reports and visualization, which can be used in the strategic decision making of the
organization. The predictive analysis is different from the data mining techniques. It is manually
guided discipline in which the data patterns are used to make forward looking predictions. The
predictive analysis delivers solution for the next step in the decision making. In this essence, the
present paper will discuss the role of the predictive analysis and the data mining techniques in
the business intelligence process of the organization.

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Data Mining
The data mining is a novel technology, which has arisen with the advent of digital mediums. The
data mining is a computational process through which patterns, trends and behavior are identified
in the large data sets. It is a complex process in which several different technologies such as
artificial intelligence, machine learning, statistics and the database systems are used in to identify
critical business information. The aim of the data mining process is to attain information
regarding the data sets and transform it for the better use in the organization. As the primary aim
of the data mining tool is to acquire business information from the database, it is also known as
the knowledge discovery in the databases (Hand, 2007).
The data mining encompasses the entire activities essential in the data discovery. The term is
used the process of collection, extraction, warehousing, statistics, machine learning and the
artificial intelligence. The statistics is an important part of the data mining as it provides the
entire tools essential in the data analysis and the machine learning process. The first step in the
data mining is the cleaning. In this process, errors and inconsistencies are removed from the data
to ensure that thee data, which will be used in the further process is consistent and authentic. The
data mining tools comprises of the automatic toolset, which can identify useful pattern in the
large data sets. The data mining searches for clues or similarity in the data (Larose, 2014). The
data mining is the first stage in designing a predictive model. The data mining process can isolate
the valuable data variables from different variables. The data mining is the process isolating the
important variable patterns, which can be identified through various different possibilities. These
variables are used to represent a mathematical model, which formalizes the relationship between
these patterns. The future behavior of the organization will be guided by these data patterns. The
traditional business intelligence tools extracts relevant information in a structured manner,