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     Importance of Data Mining in Analyzing Your Business: Trend Shows An Increased Spending
 

Importance of Data Mining in Analyzing Your Business: Trend Shows An Increased Spending

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Mining data is helping firms make major decisions and compete more effectively. Data mining has wide applications in sectors such as telecommunications,banking/finance, retailing, automobile, and ...

Mining data is helping firms make major decisions and compete more effectively. Data mining has wide applications in sectors such as telecommunications,banking/finance, retailing, automobile, and healthcare.

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         Importance of Data Mining in Analyzing Your Business: Trend Shows An Increased Spending Importance of Data Mining in Analyzing Your Business: Trend Shows An Increased Spending Document Transcript

    • Importance of Data Mining in Analyzing Your Business: Trend Shows An Increased Spending Irrespective of size, businesses are finding an edge over competition or a new niche by gaining greater insights from data. Mining customer data, reports on market analysis, sales data, and so on and making clear sense of the data is helping firms make major decisions and compete more effectively. Data analytics or data mining transforms raw data into useful information. An article in ComputerWeekly.com reports on a survey by Accenture and SAS which showed that in 2012, up to 72% of businesses in the US planned to spend more on analytics even when many other budgets were cut. Here’s a look of some of the ways in which the ability to predict trends from data has proved useful in various industries. Data Mining in the Automobile Industry The application of data mining in automotive sector can be well explained with the example of General Motors (GM). A 2012 Chevrolet Volt owner brought in his car for a warranty repair in Europe. The problem was a faulty valve which affected the working of the brakes. As a first attempt of error detection, GM analyzed the parts used in their cars, and collected its manufacturing records from the supplier. The analysis took one month and showed that only four cars in the US had a faulty valve! Data mining had saved the day. In fact, if this capability was not available, GM would have had two options to recall the model, inconveniencing thousands of owners or to let the defect slide which would have put the drivers’ lives at risk. Like GM, many automakers are using advanced track and trace software to spot defects more quickly. This is how the process works:    Each machine component is given a unique bar code or radio-frequency tag by the supplier At each assembly point, this component get scanned to collect data on how it was built If any problem emerges later, the automaker scans the component
    •  On detection of the defect, the manufacturer and the supplier trace the fault to the Vehicle Identification Number (VIN) of all other affected cars Data mining improves employee performance and reduces recall costs. According to Teradata Corp, a data analytics company, track and trace software is a cost-effective solution to cut down excess cost. The company claims as this software can lessen warranty costs by 10 to 35 percent, administration costs by 25 to 45 percent, and compliance costs by 30 percent. Data Mining in the Retail Sector Mining customer and sales data offers huge benefits for the retail industry:        To identify customer buying behavior To realize customer shopping patterns and trends Design more effective policies for goods transportation and distribution Enhance goods consumption ratios For purchase recommendation and cross-reference of items Improve the quality of customer service Analyzing customer loyalty for achieving customer retention Data Mining in the Healthcare Sector In healthcare, data mining services are becoming increasingly popular as well as essential. Physicians can identify better treatments and effective practices, healthcare insurers can detect fraud and abuse, hospitals/healthcare can make decisions on customer relationship management – all of which improves leads to better healthcare services at more affordable cost. Main applications of data mining in healthcare are:Smarter Methodologies for Treatment: - Analyzing patient and treatment data helps to identify the most effective treatment for diseases, by comparing and contrasting various causes, symptoms and the previous treatment methods. Improved Healthcare Management: Data mining can develop better diagnosis and treatment methodologies and improve and maintain the quality healthcare. It helps to identify chronic disease states, high-risk patients, and hence to identify the number of hospital admissions/claims. Better Management of Customer Relations: Customer relationships are valuable, as far as any healthcare sector is concerned. Understanding patient preferences and characteristics can improve their satisfaction level to a greater extent. Another big application of data mining is in healthcare forecasting and investigation. Drug manufacturers usually conduct studies on approved drug, to identify its side effects and to show them on the product labels. However, it is impossible to identify all adverse interactions before actual use. Research conducted by the Stanford University School of Medicine and Microsoft recently revealed that mining web searches can expose the unreported side-effects of drugs more effectively. Most people use the internet to report and share
    • information about drug use and the data mining software developed by the Microsoft scientists revealed that users of the anti-depressant, Paroxetine and cholesterollowering drug, Pravastatin were experiencing a drug-drug interaction that was previously unreported. Other industries that benefit from analyzing data trends include telecommunications and banking and finance. Such analysis requires special skills and software. That’s why many businesses are relying professional data mining services.