Data Management
Johnny48
DiscussionsNeedResponsesMIS.docxDiscussion1
1. According to the referred articles, they talk about how poor data quality is an expensive problem that damages reputation. According to the Gartner report, organizations fail to make right assumptions about the state of their data and continue to experience inefficiencies, excessive costs, compliance risks and customer satisfaction issues as a result. These listed issues effect the data quality hence impact the business. One of the articles illustrates about how the poor data quality impacts customer satisfaction to undermines a company’s reputation, as customers can take to social media to share their negative experience.
2. After referring a few articles, it guided me to understand that how Data mining, knowledge discovery, or predictive analysis mean one and the same. Data mining is nothing but a set of techniques for discovering patterns in a large data set. By making use of these patterns’ organizations create a predictive model to stay forward. In today’s world, each organization encouraging Big Data and are, hence using sophisticated analytical methods. So, the increased usage of Big Data leads the need for data mining. Both Artificial Intelligence and Machine Learning are gaining a lot of relevance in the world today, and the credit goes to Data Mining. How else do you make a system “artificially intelligent” without feeding it with relevant data and patterns? And, how do you extract relevant patterns if not by Data Mining?
3. According to referred articles, it explained the right definition of ‘Text Mining’ which states that it is used to help answer specific research questions. As it would be tedious for anyone to read all the millions of research articles on the topic themselves, so, here is where Text Mining comes into picture. It is capable of filtering large number of researches and extracts the relevant information one need. For example, within academic articles, then you can apply a text mining tool which helps extract the information you need from large amounts of contents. The tool extracts by learning how to find information from each article.
Discussion2
Quiz 1
According to Redman (2018), Poor data quality causes the decision makers in a business to fail to make proper decisions or even fail to make decision at all. Poor data may also cause a business to lose sales and other business opportunities, flawed strategies, misallocation of resources, making wrong orders, having incorrect inventory levels. Eventually, such flawed issues can make customers get frustrated and go away causing a very low business return (Haug, et al. 2013). When the customers shy away from the business, the profit level goes down and thus the business faces the risk of closedown. The cost of poor data quality spreads in the entire organization and thus affects the whole systems, the accounting and customer services (Strong, Lee & Wang, 2017). There is also an additional cost for the company because employees need to take time to hunt down the correct data and make up the errors.
Quiz 2
Data mining is the process of sorting through enormous data sets with the aim of identifying patterns and establishing relations within the data to solve problems by using data analysis methods (Hand, 2017). Data mining involves creation of association rules through data analysis for frequent patterns. According to Fayyad et al. (2016), this is followed by using a criteria that supports the data analysis to locate the most important relationships within the data. Other parameters that are involved in data mining include path analysis or sequence, clustering, classification and forecasting. For the path or sequence analysis in data mining, the analysts look for patterns where one event leads to another event (Tan, 2017). For a classification parameter, it looks for any new patterns in the vast data and might observe the way data is changing and the way it is organized.
Quiz 3
