What are the business costs or risks of poof data quality: Expand on your colleagues’ postings by providing additional insights or contrasting perspectives based on readings and evidence.
What are the business costs or risks of poof data quality?
After studying this week’s assigned readings, discussion the following:
1. What are the business costs or risks of poof data quality? Support your discussion with at least 3 references.
2. What is data mining? Support your discussion with at least 3 references.
3. What is text mining? Support your discussion with at least 3 references.
Please use APA throughout.
Post your initial response no later than Friday of week 3. Please note that initial post not completed on the due date will receive zero grade. See class syllabus for late assignment policies. Review posting/discussion requirements.
Read and respond to at two (2) of your classmates no later than the last day of week 3. In your response to your classmates, consider comparing your articles to those of your classmates. Below are additional suggestions on how to respond to your classmates’ discussions:
· Ask a probing question, substantiated with additional background information, evidence or research.
· Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.
· Offer and support an alternative perspective using readings from the classroom or from your own research.
· Validate an idea with your own experience and additional research.
· Make a suggestion based on additional evidence drawn from readings or after synthesizing multiple postings.
· Expand on your colleagues’ postings by providing additional insights or contrasting perspectives based on readings and evidence.
Read and respond to at two (2) of your classmates: 150 words
Business costs and risks odata quality
Information technology today has been able to assist businesses extensively when it comes to collecting and storing customer data in systems. According to Laranjeiro, Soydemir & Bernardino (2015), organizations are storing staggering amounts of data on a regular basis, and often it is seen that collecting large volumes of information can take a toll on quality due to poor management. As more complex data is getting stored in various files and databases, the storage keeps piling up and because of that assuring quality and reliability of that information continuously decreases (Hazen et al. 2014). It has been studied that organizations often store a mountain of data in local drives and storages and the definitions of these data along with the formats are often incorrect, giving rise to inconsistencies.
When the quality of data becomes poor in a given organization, liability increases as one data is often linked to the other. A shortage of accuracy and quality in one part of the information will cause a ripple effect upon other data and companies will discover this upon further investigation. Hampering the quality of data can cause severe impacts upon the economic and social balance of an organization. An organization exists to provide products or services to customers, and a lack of quality data can damage the business proceedings leading to less customer satisfaction. A company will not also be able to keep a proper tabulation of the costs that are being incurred, and annual reports will have terrible flaws. In the words of Saha & Srivastava (2014), the organizations collect data to make better decisions regarding the progress of the company and lack of proper information can have an impact upon the decision-making process leading to further failures. The costs of operation in a given organization can increase extensively as a lot of financial input along with time must be provided to improve the quality of the data that has reliability issues. This, in turn, sabotages organizational cultures and the company experiences slow growth.
It is a process through which specific patterns existing in vast volumes of data, are extracted to have a better understanding of situations. According to Larose & Larose (2014 organizations collect raw data which must be processed so that they can gather knowledge or insight regarding the architecture of the market that is being targeted. This process involves the use of software that can make interpretations and pattern analysis in a data pool so that useful information is delivered at the end (Witten et al. 2016). Organizations pay active attention to the process of data mining as analyzing the data helps in better understanding of the customer needs and demands. When a higher knowledge regarding the preferences of the customers is procured, the businesses can formulate such strategies that can grab the market and solidify the customer loyalty in a better manner.
It is a method through which huge piles of unstructured texts are analyzed and explored to grab better concepts, patterns, keywords and all the other possible attributes that the mining process can extract (O’Mara-Eves et al. 2015). Data scientists have stated the high demands of developing big data through the algorithm process that can better inspect the enormous chunk of unstructured data. According to Nassirtoussi et al. (2014), the central aim behind this process dwells upon organizations intending to gather more mature insights when it comes to gaining knowledge from documents, emails, the logs in call centers, posts on social media and even the medical records. Organizations have introduced the features of text mining in the artificially intelligent chatbots and other virtual assistants that provide customer service and gather information at the same time.
Risks of poor data quality:
Data is eligible for borrowers with data suppliers; we understand the system of observations. Supervisory design for direct data selection to select the credits used to ensure that the buyer’s data is suitable for their organizations. In these ways, these symptoms do not theoretically be theoretically chosen or gradually selected by experts. The ability of the observation process receives consumer voice. Similarly, managers can find properties that cannot view enough data. (Wang, & Strong, 1996). The accuracy or performance of the results cannot be corrected as it does not appear within the basic rules.
Experts use data that is not constantly cleaned, since it requires time and effort to clean and configure the dataset for validation. This affects the mixed dignity used to study and, if necessary, can produce seemingly spectacular results. If they were to be examined, they would be available to examine, why should there be a respectable viewpoint, and why should you not lose respect? (Mubaghba, Foster, Thabane, & Cheng, 2017)
Data collected before data collection for other potential customers has to be shared or collected data sharing data. The data needed for remote data or travel is not entirely separate, we see, and put a legitimate disc in a professional. The above cases occur in a frame of persistent continuous communication, from one viewpoint, to another, with sinless and constructed analytical information. While it is not possible for other people to believe it, we are grateful that the stars want others to get and use their data. (Drew, Wilks, Wilson, & Kennedy, 2016). Now it is an ideal opportunity to take into consideration every single clinical study of sensory techniques of data exchange and clinical trials.
What is Data Mining?
Data mining is the quality and skill of finding the basic discovery samples from data. There is a wide assembly of images, which can be found in the data. There are clear structures or complex, which help to find a considerable number. Data mining has been used to separate data with data mining. Three clear structures of information flow are aimed at determining their ability to collect events. The diagram shows that material mines can be used to combine scenes with the sequences in a program that identifies one another. An effective structure that allows to effectively overcome the obtained markup data and test the basics. Finally, point mining can only be changed to text data according to the mandatory conclusions relating to wireframe designs, however, packages can be used to give training bit for purposes behind the scenes to work. (Sri, Guan, Jurad and Manikas, 2017)
What Is Text Mining?
Full text of text processing is not much available, how does one person cooperate with it? However, the text indicates that the text attempts to indicate and which scriptures may require more specific data. By examining important messages on this topic, the loss of the text will reduce human responsibilities. Moreover, since the beginning, and the way they have not been removed too much, to understand what is happening with customers regarding Samsung Galaxy S3, it’s only checking some odd one of the 201 structures only when it’s needed. In this research, some things came out. Despite this, this thing has been especially restored to a wide range of hard officers. Despite this, they do not have to pay attention to the fact that they pay an extraordinary personality plastic cover at the back and do not pay attention to the fact that the broadest edge of the public does not have to continue to show the processor the cross memory is an excellent time and quality camera when they opted for Sony XperiaTM to close the fund in the game. Different respondents abandoned battery life and support. Some of them are equally discrete and Nokia. The lovely thing that comes to mind is the fact that the iPhone is more attracted to the relentless people, the epic curiosity with the iPhone is called, and the phone has a problem in its more authentic screen scenario. Similarly, it was noticed that anyone cannot support anyone with that phone.