Week 3 Discussion Forum (click to read instructions)
After studying the assigned reading for the week, discuss the following:
1. What are the business costs or risks of poor 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.
Use APA at all times.
Post your first response no later than Friday of the third week. Please note that the first post not completed by the due date will be scored zero. Please refer to the class syllabus for late assignment guidelines. Check posting/discussion requirements.
Read and respond to two (2) of your classmates no later than the last day of week 3. In your response to your classmates, compare your articles with those of your classmates. Below are additional suggestions on how to respond to your classmates' discussions:
· Ask a probing question, supported with additional background information, evidence or research.
· Share insights from reading your peers' posts and summarize the information to provide new insights.
· Provide and support an alternative perspective by reading from the classroom or from their own research.
· Validate an idea with your own experience and additional research.
· Make a suggestion based on additional evidence obtained from the readings or after synthesizing various publications.
· Increase the contributions of your peers by providing additional information or contrasting perspectives based on reading and evidence.
Read and answer two (2) of your classmates: 150 words
Business costs and data quality risks
Information technology can now comprehensively help companies collect and store customer data in systems. According to Laranjeiro, Soydemir & Bernardino (2015), organizations regularly store staggering amounts of data and it is often shown that collecting large amounts of information can compromise quality due to poor management. As increasingly complex data is stored in different files and databases, the stores continue to accumulate, causing the quality and reliability of this information to continually decline (Hazen et al. 2014). It has been studied that organizations often store mountains of data on local drives and storage and the definitions of this data along with the formats are often incorrect, leading to inconsistencies.
When data quality degrades in a particular organization, liability increases as the data is often linked to others. Lack of accuracy and quality in one piece of information will affect other data, and companies will discover this in further investigation. Poor data quality can have serious repercussions on 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 hamper business operations and lead to lower customer satisfaction. A company will also be unable to maintain a proper statement of expenses incurred and the annual reports will be terribly flawed. In the words of Saha & Srivastava (2014), organizations collect data to make better decisions about the progress of the company, and the lack of adequate information can affect the decision-making process and lead to more failures. Operational costs in a given organization can increase significantly as a large amount of financial input must be provided along with time to improve the quality of data with reliability issues. This, in turn, sabotages the company culture and the company grows slowly.
It is a process by which specific patterns present in large amounts of data are extracted to better understand situations. According to Larose & Larose (2014), organizations collect raw data that needs to be processed so that they can gain insights or perspectives on the architecture of the target market. This process involves the use of software, interpretations and analysis of patterns in a data set so that useful information is ultimately provided (Witten et al. 2016) Organizations pay active attention to the data extraction process, as the Data Analysis Helps Identify Needs To better understand customer needs and preferences, companies can formulate strategies that can conquer the market and better build customer loyalty.
It is a method used to analyze and sift through huge stacks of unstructured text to find better concepts, patterns, keywords, and any other possible attributes that the mining process can extract (O'Mara-Eves et al. 2015). Data scientists have outlined the high demands of big data development through the algorithm process, which can better examine the huge portion of unstructured data. According to Nassirtoussi et al. (2014), the central objective of this process is focused on organizations that aim to obtain more mature insights when it comes to extracting knowledge from documents, emails, call center records, social media posts, and even medical records. Organizations have introduced text mining capabilities into AI-powered chatbots and other virtual assistants that provide customer service while collecting information.
Risks of poor data quality:
Data is creditable to borrowers at data providers; we understand the system of observations. Oversight design for direct data selection to select credits used to ensure buyer data is appropriate for their organizations. In this way, these symptoms are not selected theoretically or gradually selected by experts. Observation process capability gets the voice of consumers. Also, administrators may encounter properties that cannot display enough data. (Wang & Strong, 1996). The accuracy or performance of the results cannot be corrected as it is not included in the basic rules.
Experts use data that is not constantly cleaned because it takes time and effort to clean and configure the data set for validation. This affects the mixed dignity of the study and can produce spectacular results. If they were scrutinized, they were available for scrutiny, why should there be a respectable point of view, and why not lose respect? (Mubaghba, Foster, Thabane & Cheng, 2017)
Data collected prior to data collection for other prospects must be shared or collected in order to exchange data. The data necessary for remote data or travel is not completely separated, let's see and put a legitimate disk in a professional. The previous cases occur in a framework of persistent and continuous communication from one point of view to another, with constructed analytical information and without sin. While other people may not believe it, we're thankful that stars want others to receive and use their information. (Drew, Wilks, Wilson, & Kennedy, 2016). Now is an ideal opportunity to consider each clinical study of sensory data exchange techniques and clinical studies.
What is data mining?
Data mining is the quality and ability to find the fundamental discovery samples from the data. There is a wide collection of images found in the data. There are clear or complex structures that help to find a significant number. Data mining has been used to separate data with data mining. Three clear information flow patterns are intended to determine your ability to collect events. The diagram shows that the material mines can be used to combine scenes with the sequences into a mutually identifiable program. An effective structure that makes it possible to effectively overcome the received marking data and test the basics. After all, point mining can only be changed to text data according to the mandatory inferences related to wireframe designs. However, packages can be used to give training bits to make them work behind the scenes. (Sri, Guan, Jurad and Manikas, 2017)
What is text mining?
The full text of the word processor is not available, how does a person work with it? However, the text indicates what the text is trying to indicate and what scriptures may require more specific dates. When examining important messages on the subject, losing the text will reduce human responsibility. To understand what is going on with customers regarding the Samsung Galaxy S3, it is checked from the beginning and since not too much has been removed, just an odd one out of 201 structures only when necessary. A few things came out of this investigation. However, this thing was specially restored for a variety of tough officers. Despite this, they do not have to pay attention to the fact that they pay attention to an exceptional personality plastic cover on the back and do not pay attention to the fact that the general public does not have to continue to show the manufacturer the cross memory . It's an excellent time and the quality of the camera they choose for Sony XperiaTM decided to close the bottom line in play. Several respondents gave up on battery life and support. Some of them are just as discreet as Nokia. The beauty that comes to mind is the fact that the iPhone is more drawn to the relentless people called Epic Curiosity with the iPhone and the phone has a problem with its most authentic screen scenario. Likewise, it was found that no one can support anyone with this phone.
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