Task1:Complete the following assignment in one MS word document:
Chapter 5 –discussion question #1-4 & exercise 6 & internet exercise #7
Chapter 6– discussion question #1-5 & exercise 4
When submitting work, be sure to include an APA cover page and include at least two APA formatted references (and APA in-text citations) to support the work this week.
All work must be original (not copied from any source).
Task2:please provide replies to below student post each in 130 words.
ankita-1. What are the business costs or risks of poor data quality?
Maintaining data quality is an ongoing problem these days.As nobody can predict the future, companies are storing huge volumes of data. However, data quality is neglected and thus results in a significant risk to many businesses. As everybody knows data is used in all the activities of companies, which can also be used to take proper decisions at times, so poor data quality can have negative impacts on the efficiency of an organization.[Haug,2011] Since the companies are collecting and storing large volumes of data, if the volume of data increases the complexity of managing the data will increase, which means the risk of poor data quality increases. Poor data quality also results in costs to the business since resources have to spend time on analyzing and correcting errors.[ Stephanie,2017] Since data is created daily for every single operation in the company, data is a significant donor to the business culture. So with poor data quality, a business can be impacted financially, less productivity, and unable to take proper decisions, and lost customer satisfaction.[David L]
- What is data mining?
Data mining is the process of searching large volumes of data to discover hidden patterns which go beyond simple analysis. To perform the search, data mining uses mathematical algorithms to segment the data and evaluate the patterns.[ Jiawei H,2000]
Properties of data mining are:
A· Automatic discovery of patterns
B· Creation of actionable information
C· Prediction of outcomes
D· Focus on databases[Callan,2004]
- What is text mining?
Text mining is a process of extracting meaningful information from text. It can also be referred as a processing of text to extract information that is useful for a purpose.[Hearst,2003] Text mining also works with unstructured, semi-structured data such as emails, HTML documents, text files etc. Unlike data mining, text mining extracts patterns from the text rather than databases. Text mining is actually the process of structuring the input text and extracts the patterns with it.[Callan , 2004]
mohan-Question 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.
Question 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.
Question 3
With regard to Aggarwal & Zhai (2012), text mining is the process of keenly exploring and making an analysis of vast amounts of texts that are unstructured. This process involves the aid of software that has the ability to identify patterns, concepts, topics, keywords and other data attributes within the vast text (Berry, 2014). This process is also referred to as text analytics. Text mining has recently been a popular aspect for scientists and other users because there has been the development of deep learning algorithms and big data platforms that aid in the analysis of massive sets of unorganized data. According to Feldman & Sanger (2017), mining and analyzing texts is important because it helps an organization to get insights into potentially valuable business ideas in customer emails, corporate documents, verbatim survey comments, call center logs and social network posts among other text sources.