discussion board response

respond to ryan in 100 words
Ryan Mason
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Data analytics is defined as “the science of examining raw data, removing excess noise from the data set, and organizing the data with the purpose of drawing conclusions for decision making.” (Richardson, et al., 2021, pp. 251). Data analyst s provides a way for businesses to cipher through big data. Big data is information too large for a company or single individual to comprehend or correctly apply by themselves. The technology behind data analytics makes big data (Raw data) usable for companies. The complexity revolved around big data makes it almost impossible to navigate. This is where data analytics software and processes become effective.
Data analytics has many great aspects but can also be costly. First, it can be very expensive to prepare a software or process that is able to decipher the large amounts of data being obtained. It is also expensive to produce the data itself. These costs sometimes steer companies away from attempting to use, process, and produce these large amounts of data. However, applying data analytics could vastly improve a business’s strategic business planning. It directly affects the success and operational capabilities of an organization. “In addition to producing more value externally, studies show that Data Analytics affects internal processes, improving productivity, utilization, and growth.” (Richardson, et al., 2021, pp. 252). Data Analytics can be applied to many different products and markets as well. “Data Analytics is used in many different areas such as biology, econometrics, epidemiology, social science, social media, cyber security, and so on.” (Angelov, et al., 2017). Ultimately, data analytics is a great tool for any business to apply.

respond to Christiana Whisker in 100 words
First, I want to explain what business analytics are. There are a few different ways that we define and explain just what it is. The way that our textbook defines it is, “we define business analytics as the science of examining raw data, removing excess noise from the dataset, and organizing the data with the purpose of drawing conclusions for decision making. Data analytics is useful for a business to examine patterns and trends in large datasets.” (Richardson et al., 2021. p.251) There are many different ways that accountants can use data analytics to help improve different business processes. One of them being they can help manage the risk that a business might take and even manage the setbacks that it may suffer. Another one being to help enhance security, help each customer get a personalized experience, or even give some influence when it comes to making decisions. While doing some research, I found an article that explains data analytics as, “it’s a process that, when utilized correctly, provides a 360-degree view of the problem being solved, allowing decision-makers to make the best decision with the best information available. Accountants use data analytics to help businesses uncover valuable insights within their financial statements, reduce costs, identify process improvements that increase their efficiency, and better manage risks. Prior to the growth in data analytics, enabling a business or clients to reach their goals has been a manual and time-consuming process based predominantly on institutional knowledge and relationships. By understanding and mastering data analytics, accountants can future-proofing their career, expediting the learning curve, regardless of the career path they choose. Professionals in public accounting can use these analytical skills to make sense of the massive quantities of financial information available to evaluate business performance, identify and manage risk, and analyze customer behavior to anticipate market trends more efficiently and accurately than ever before.” (Castonguay, 2021)

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