1) Whatare the business costs or risks of poor data quality? From past fewdecades Information technology has been growing so fast due to rapid changes inbusiness requirement.
Every business needs to maintain a data structuresincluding past and present to handle the business day to day transactions. Datais a important keyword in business world and to arrange that all data in aformal order is another burden. To maintain quality data is very important ifdata mismatched then business may get fail in planning and decision making.
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Ifthe data volume increased then there is a risk of data complexity. In recent daysorganisations are preferring larger and complex set of information this meansthat risk of poor data quality increases. Poor data maintenance can imply hugesequence of negative consequences which may harm the reputation or goodwill ofthe company.
Poor data quality of the organisation also increases theoperational costs because time and efforts are spent detecting detecting andcorrecting errors. Data are the critical and very important inputs almost tothe all business, it helps in planning and decision making. In most ofthe cases corporate leaders are always busy to capture useful business data asa priority. The challenges imposed by taking the quality data can be dauntingthe advantages and chances that qualitative data enable and help to improve thequality so that business can directly use that information in decision makingprocess.
Poor data quality is a huge problem for many organisations. Benefits of good quality data: · Betterthe data quality, the more confidence management will get in decision making· Goodquality data allows more productivity to the staff· Helpto meet targets as per the business requirements· Moreaccurate output Costs of poor data quality: · Companiesreputation may damage· Lostrevenue· Theywill missed greater opportunities· Lowoutput 2) Whatis data mining? Data is aformal way of gathering the information depends on the business needs. Toarrange that informal information into a meaningful and formal way is called asinformation. Data is a set of raw materials in unsystematic order.
Organisations needs to convert that data into a meaningful information. Datamining is a technique which helps the business how to find the useful knowledgeor information in all that data preprocessing pattern. Data mining is nothingbut the classification and gathering of data. Datamining is a gathering of data which helps the business in various applications.Data mining helps in discovering knowledge from various data collected byorganisations. The primary objective of data mining is gather the useful andeffective information from large data sets and provide better decision makingpolicy for business.
3) Whatis text mining? Textmining is a process to convert unstructured information into a meaningfulformat so that enterprises are readily capture the available data. Text miningis a analysis of data stored in natural language format. It helps to solvebusiness problems by using various techniques. Text mining use text analyticsoftware which helps by transposing words and phrases in unstructured data intonumerical values.
The major objective of text mining is to process the textualinformation into a meaningful indices from the text so that it will be easilyaccessible to all. Themotivation behind Text Mining is to process unstructured (literary) data,separate significant numeric lists from the content, and, accordingly, make thedata contained in the content open to the different information mining (factualand machine learning) calculations. Data can be removed to determine synopsesfor the words contained in the archives or to register outlines for the reportsin view of the words contained in them. Consequently, you can dissect words,groups of words utilised as a part of reports, and so forth., or you couldexamine records and decide likenesses between them or how they are identifiedwith different factors of enthusiasm for the information mining venture.