Data Quality, Text and Data Mining Response Post 1. What are the business costs or risks of poof data quality? poor quality of data may create huge loss to

Data Quality, Text and Data Mining Response Post 1. What are the business costs or risks of poof data quality? poor quality of data may create huge loss to companies. Because these days companies depend on data to take decisions. Companies use different sources to get data or develop internal database. Till date companies find difficult to maintain high quality of data. There re barriers in company which makes it difficult to maintain the data quality. Fitness for the use is what the quality defines, how far the available data is been used in terms of authenticity and believability and usefulness are contextual quality of data, which is being ignored. Four major types of data quality are verified, accuracy, timeliness, completeness and consistency. Major problems in organizations about poor quality of data would be, relevancy, completeness, format and other issues like security, privacy and ownership. Having these barriers companies may face difficulties in finding right methods to decode the data. Consequences will impact the economic and social factors and cause the lower customer satisfaction and job satisfaction and reduce the performance of company. 2. What is data mining? It is computational process which analyzes the large amounts of data to identifying the patterns and useful information to take decisions. Data mining is widely using tool in recent days. From data to knowledge different data mining technique are used in different industries. Using data mining techniques, identifying the patterns will. be done these patterns will be used to take decisions at required times. Some of the data mining techniques are used to identify the frauds that happening in different industries. In banking sector we can see frauds like mis using credit cards or debit cards, these can be identifies using these techniques.3. What is text mining? Process of deriving high quality of data from text. This is used in different ways, where human generated text is available. Example in market research to understand the customer satisfaction or review about nay product they no need to prepare a questionnaire, they can go to websites where people post their reviews, using text mining techniques they can understand the product reviews and get the wanted information to take future decisions about the product. Converting unstructured data into structured data is what happens in text mining.