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Data Mining And Its Relevance

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					                                       Data Mining and Its Relevance

Data mining can be defined as the process of extraction of meaningful patterns and relationships from data
resources, for instance texts, the web and other databases. It is different from what is known as QLAP, SQL data
warehousing. The process makes use of statistical and pattern matching methods. Data mining also borrows from
machine learning, information retrieval, data visualization and many more.

Today multiple verticals of science, business and other types of platforms that involve huge amount of data, are
required to be transformed into something knowledgeable and meaningful. There are several website owners
along with SEO professionals that utilize various statistical packages to make their data more useful and
meaningful. At the same time, data mining at times is overlooked by certain organizations when the process has
the capacity to offer statistical procedures and interesting data that offers you a greater control.

It has been observed that the data we have is most often noisy and vast. This means that it is not precise and that
the data structure is intricate. Other concerns related to data mining include missing values, sparse data, static
data, dynamic data and issues regarding algorithm efficiency,heterogeneity, interestingness and relevance. The
process of data mining includes the following aspects:

         Recognizing the data resources and selecting the target data
         Pre-processing that includes cleaning and attribute selection
         Data mining that would extract patterns and models
         Post-processing that includes recognizing interesting and meaningful patterns

Data mining helps the enterprises to analyze the information from various perspectives and utilize it to enhance
target consumer services, maximize revenue generating opportunities and minimize the marketing and sales
expenses. Government's, huge MNC’s, private companies and other types of businesses today aim for huge
volumes of data collection. The principal objective behind this is business and research development. It is crucial to
note that the process of data mining might take a long time to find and search for data from databases, websites
and other internet resources.

In order to make the process easy, eminent service providers of B2B marketing automation solutions have
introduced data mining software that helps in lead generation and new business development. Other benefits
offered by the software includes the following:

         Generate revenue with greater qualified leads
         Maximize the marketing and sales efficiency and effectiveness
         Helps in demonstrating accountability and value to management
         Helps to align sales and marketing focus and delivery

Leading solution providers data mining solutions with an integrated lead generation environment also integrates
online visitor tracking and behavior analysis to offer a multi-dimensional view of scopes, buying prospects and
leads. Furthermore, the solution helps in converting prospect and consumer data into business intelligence.

Also read more on - Lead Scoring Model, marketing funnel

				
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Description: Data mining can be defined as the process of extraction of meaningful patterns and relationships from data resources, for instance texts, the web a