Discussion of Analytics

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There are three main types of analytical techniques: descriptive, predictive, and prescriptive. Each type of analysis has its own strengths and weaknesses, and it is important to choose the right technique for the job at hand.

Descriptive analytics is all about understanding what has happened in the past. It involves collecting data and then using that data to generate insights. For example, a company might use descriptive analytics to understand patterns in customer behavior. By analyzing data on customer purchases, interactions, and other behaviors, companies can gain insights into which customers are most loyal, what motivates them to buy, and what factors influence their decision-making. This information can then be used to tailor marketing and sales strategies to better meet the needs of specific customer groups (Frankenfield, 2020).

Predictive analytics takes things one step further by using historical data to make predictions about what will happen in the future. For instance, a retailer might use predictive analytics to predict how demand will change over the course of a month. Then there is prescriptive analytics, which makes use of machine learning, goes beyond predictions and actually prescribes a course of action. In other words, it tells you not only what will happen, but also what you should do about it. For example, a company might use prescriptive analytics to optimize its marketing campaigns. By analyzing data on customer demographics, purchasing habits, and previous responses to marketing campaigns, the company can develop a more targeted and effective marketing strategy (Segal, 2021).

All three types of analytics play an important role in business decision-making. The key is to choose the right type of analysis for the question you are trying to answer. But, ultimately, prescriptive analytics provides the most powerful tool for companies that are looking to improve their performance and achieve their goals.

2

The role of business analytics has become increasingly important in the modern business world. As data increasingly drives decision-making, businesses need analysts to help make sense of this data and provide insights that can guide strategic planning. While some organizations choose to keep their business analytic functions separate from their strategic planning processes, there are several compelling reasons why it makes sense to integrate the two (Shanks & Bekmamedova, 2012).

For one thing, analysts are uniquely positioned to identify trends and patterns in data that can inform strategic decisions. They are trained in the art of data interpretation. They understand how to identify patterns and trends in large data sets, and how to use this information to inform strategic decisions. In today's data-driven world, analysts play an increasingly important role in helping organizations make sense of the vast amounts of information that they collect. By understanding how to effectively interpret and use data, analysts can help organizations make more informed decisions about everything from product development to marketing strategy. In many cases, analysts are the ones who are able to see the big picture and identify trends that others might miss (Sedon et al., 2017).

In addition, analysts can work with planners to develop quantitative models that can be used to assess the potential impact of different strategies. Finally, by bringing together planners and analysts, organizations can ensure that data is used effectively to drive decision-making at all levels....

…decision-making. There are a variety of tools and techniques that analysts can use to conduct business analytics, including data visualization, regression analysis, and machine learning. Data visualization helps analysts to understand complex data sets by creating graphical representations of the data. Regression analysis is a statistical technique that can be used to identify relationships between different variables. Machine learning is a type of artificial intelligence that can be used to automatically detect patterns in data. By using these tools and techniques, analysts can gain valuable insights into how businesses operate and identify areas for improvement (Shmueli et al., 2017).

In my future position as a manager, I expect that business analytics will be a valuable tool for understanding what is happening within my organization and making informed decisions about where to go next. The first step I would take as a manager would be to gather data from a variety of sources, including financial reports, customer surveys, and employee feedback. Once I have this information, I can begin to look for patterns and trends. This can help me to identify problems and opportunities, and to develop strategies for addressing them. For example, if I notice that my companys sales are lagging behind those of our competitors, I could use business analytics to investigate the reasons why. Perhaps our prices are too high or our product mix is not ideal. Perhaps our marketing is off based on demographics and consumer values. Whatever the case may be analytics could help me to more clearly understand the factors at play (Delen, 2014). By using the tools of business analytics, I could gain insights…