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1. Examine Business cost or dangers because of poor data quality: Issue with giving us a data quality is a constant issue that torments different associations , and on the off chance that IT pioneers don't make sense of how to improve the accuracy of their data, that could be dead genuine results. There are different ways that associations submit mistakes with get-together and providing a client data. Human goof is a significant one. For instance, when a client is altering a business' site, he or she may present a rash bungle, for example, incorrect spelling a word, giving an outdated address or giving the wrong telephone number. Once these goofs are added to the system, they can be hard to changes. They can also induce entire deals. Associations depend upon correct data to help their displaying, and client advantage tries. 2. Data Mining: Data mining is a technique used to expel usable information from a more prominent arrangement of any undefined data. It reasons separating from data in far reaching cluster of data utilizing and not less than of one programming. 2) Datamining has applications in different fields, similar to science and research. As a use of data mining, associations can take in extra about their clients and build up all the systems, identified with different business limits and also use assets in prefect and savy way. This urges associations are nearer to their goal and settle on better choices. Data mining intense data collecting and warehousing and also PC arranging. For this, data and reviewing the future occasions, data mining uses advanced numerical counts. Data mining is called Knowledge Discovery in Data. 3. Text Mining: Text mining is sort of records mining, without that records mining devices are after treat with based data long with databases, it prints content also execute painting along unstructured then semi-dependent data units text messages, files and HTML reports and consequently forth. Here, final results are text mining is a miles higher. Text mining is the conduct in regards to organizing put to printed setting (regularly parsing, aggregately with the summation over a temperate derived text mining then it removes on others, yet consequent application among a database), determining designs inside the organized data, through out the evaluation then money concerning the yield. References 1) Hakkinen,l., & Hilmola,o-p.(2008). ERP evaluation During the shakedown Phase: Lessons from an after-sales division.Information System journal, 18(1), 73-100. 2) U.M Fayyad and R. Uthurusamy (eds.). Proc. !st Int. Conf. Knowledge Discovery and Data Mining (KDD'95), AAAI Press,Aug.1995. 3) Redman, T.C Data Quality for the Information Age. Artech House,Bostaon, MA,1996