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Unlocking Business Insights: Strategic Applications of Data Mining Techniques

   

Added on  2019-09-23

9 Pages2725 Words169 ViewsType: 169
Data Science and Big DataArtificial IntelligenceBioinformaticsStatistics and Probability
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Running Head: Blog writingBlog writing
Unlocking Business Insights: Strategic Applications of Data Mining Techniques_1

2Blog writingData Mining Techniques-Importance of Data MiningTechniques29th June 2019Data Mining Data mining can be defined as the process which helps in discovering several patterns inlarge sets of data involving techniques of intersecting statistics, machine learning, and adatabase system. It is an in a disciplinary sub-category of statistics and computer science. Itaims at extracting information along with intelligent methods from a set of data andtransforming the same into a comprehensive structure which could be used for otherpurposes. In discovering knowledge on the database, the role of data mining is quiteanalytical. It is basically the analytical step which involves data management and databasemanagement. It also involves model, data pre-processing, and inference considerations alongwith complexity consideration, intersecting risk metrics, visualization, post-processing ofinvestigated structures and online updating. Data mining has a wide scope in analyzingdifferent sets after gathering and transforming them. Sometimes we get confused by datamining and data analysis. These two concepts are quite different from each other. Dataanalysis is applied to hypothesis and test models on the data set. For example, data analysis ismainly used in analyzing marketing campaign effectiveness irrespective of the quantity ofdata. On the other hand, we can see data mining makes the use of statistical models andmachine learning to investigate and reveal hidden patterns in a large quantity of data.The main aim of data mining is to extract knowledge and patterns from a huge volume ofdata. It is not only limited to the extraction of data. It is frequently used in referring to largevolume data or the process of collecting, extracting, warehousing, analyzing, and producingstatistical information. It is also equally applicable to the domain of decision support systemof computer and machine learning along with business intelligence. In the domain of artificialintelligence, the use of data mining can be observed. It can be said that data mining is a semi-automatic task or an automatic analysis of the huge volume of data with the aim of extractinginteresting patterns and unknown patterns of data records, dependencies, and unusual records.
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3Blog writingHere, the dependencies mean sequential pattern, mining, and rule mining. On the other hand,unusual records indicate anomaly detection of several groups of data records. Severaldatabase techniques are involved in spatial indices. Database techniques are found as asummary of the entire input data which could be used in predictive analysis and machinelearning. Data mining process or step identifies several groups within the data which could beapplied to gather more comprehensive and accurate predictions on the basis of the decisionsupport system.Data Mining TechniquesThere can be several data mining techniques which are used to cater to specific businessproblems and to come up with a different insight. It is very important to identify theparticular type of business issue or problem which is to be solved with the application of datamining techniques. If the business problem is identified accurately, it should be quite easier toselect the particular data mining technique which could be useful in yielding best results.Today's world has become quite digital in nature. People are surrounded by huge quantities ofdata. It could be forecasted that there would be a rapid growth of 40% per year in the comingdecade. But there is a challenge in this \rapid growth. The population is slowly drowning indata but people are starving for accurate knowledge. The basic reason behind this is the factthat all the data which are created are difficult to get processed. The failing initiatives to bigdata have generated huge amorphous data. The basic knowledge is buried inside. If people donot have the strength of powerful techniques and tools of mining such data, it would behighly challenging for them to gather benefits from the data. There are some of the datamining techniques which can help the business organizations and the entire population todevelop optimal results to some particular problems.The data mining techniques help in the analysis of different data from different angles andperspective. Now, we can have the knowledge to develop our decisions on the selection ofthe best-suited data mining technique so as to summarise data and come up with usefulinformation. It is very important that the information which we develop with the applicationof any one of the data mining techniques can be applied in solving different businessproblems. These techniques are highly important because actually help in analyzing theproblems and identifying the workable solutions which could not only increase the revenuesof the business but also could increase customer satisfaction and decrease unwanted operatingand business costs. Furthermore, these techniques have been introduced after several
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