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The topic of Graded Discussion Board:

 

There is an opinion that data mining may be replaced by the big data the new and emerging concept. You have to give your concise opinion after learning about both topics with the reason to justify your opinion.

If you have any other possible alternate of data mining it will also be welcomed but with solid reasons of being a replacement.

 

Note: Try to provide precise (5 to 7 lines), to the point answer and avoid irrelevant/unnecessary details.

 

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Replies to This Discussion

complete GDB

Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, search, sharingstoragetransfervisualizationquerying and information.

Data mining is the process of analyzing data from different perspectives and summarizing it into useful information, information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.

Data mining is primarily used today by companies with a strong consumer focus - retail, financial, communication, and marketing organizations. It enables these companies to determine relationships among "internal" factors such as price, product positioning, or staff skills, and "external" factors such as economic indicators, competition, and customer demographics. And, it enables them to determine the impact on sales, customer satisfaction, and corporate profits. Finally, it enables them to "drill down" into summary information to view detail transactional data.

Data mining techniques are used in a many research areas, including mathematics, cybernetics, genetics and marketing. Web mining, a type of data mining used in customer relationship management (CRM), takes advantage of the huge amount of information gathered by a Web site to look for patterns in user behavior.

Concluding the above discussion, big data is the asset and data mining is the handler of that, which is used to provide beneficial results.

In the given GDB that data mining may be replaced by the big data the new and emerging If you have any other possible alternate of data mining it will also be welcomed but with solid concept. I totally Disagree with this, Because these two concepts relate each other but are not the same thing.

Big Data is explosive growth of data of an organization. But the Data Mining is tool and technique used in softwares, that we imply to make sense of data.

So, In my Opnion Big Data is problem and solution is Data Mining. Therefore, Data Minig Technique cannot be changed with the concept of Big Data.

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Data Mining is an analytic process designed to explore data (usually large amounts of data - typically business or market related - also known as "big data") in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns to new

Big data and data mining are two different things. Both of them relate to the use of large data sets to handle the collection or reporting of data that serves businesses or other recipients. However, the two terms are used for two different elements of this kind of operation.

Big data is a term for a large data set. Big data sets are those that outgrow the simple kind of database and data handling architectures that were used in earlier times, when big data was more expensive and less feasible. For example, sets of data that are too large to be easily handled in a Microsoft Excel spreadsheet could be referred to as big data sets.

Data mining refers to the activity of going through big data sets to look for relevant or pertinent information. This type of activity is really a good example of the old axiom "looking for a needle in a haystack." The idea is that businesses collect massive sets of data that may be homogeneous or automatically collected. Decision-makers need access to smaller, more specific pieces of data from those large sets. They use data mining to uncover the pieces of information that will inform leadership and help chart the course for a business.

Data mining can involve the use of different kinds of software packages such as analytics tools. It can be automated, or it can be largely labor-intensive, where individual workers send specific queries for information to an archive or database. Generally, data mining refers to operations that involve relatively sophisticated search operations that return targeted and specific results. For example, a data mining tool may look through dozens of years of accounting information to find a specific column of expenses or accounts receivable for a specific operating year.

In short, big data is the asset and data mining is the "handler" of that is used to provide beneficial results.

Data mining is used today in a wide variety of contexts – in fraud detection, as an aid in marketing campaigns, and even supermarkets use it to study their consumers.

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