Analytics is used in all business roles. In management, it is important to under

Analytics is used in all business roles. In management, it is important to understand what type of analytics to employ depending on your position and the data available. To analyze business trends, an HR manager will look at market trends and hiring data like salaries in their local market to be competitive and attract talent.
Respond to the following:
How is data analytics different from statistics?
Analytics tools fall into 3 categories: descriptive, predictive, and prescriptive. What are the main differences among these categories? Explain how businesses use analytics to convert raw operational data into actionable information. Provide at least 1 example. Consider your role in the organization you work for (or another organization you’re familiar with). How is data analytics important to your job and your organization? If it is not, how could you and the organization use data analytics to improve performance? Respond to the prompt above in a minimum of 175 words.
Reply to these two classmate’s statements below whether you agree or disagree. State why and explain. or your faculty member. Be constructive and professional. You will respond in 100 words each statement.
1)Good morning,
Data analysis focuses on interpreting and making sense of data, such as finding patterns and insights. In contrast, statistics involves collecting, organizing, and analyzing data to draw conclusions or make predictions based on probability theory. Data analysis is more about understanding the data, while statistics involves using data to draw conclusions. Descriptive, predictive, and prescriptive analytics are the three main categories of analytical tools. Descriptive analytics focuses on summarizing data to understand past events, predictive analytics uses data to forecast future outcomes based on patterns and trends, and prescriptive analytics recommends actions to optimize outcomes based on predictions. Each category serves a unique purpose: descriptive explains what happened, predictive anticipates what might happen, and prescriptive advises on what actions to take.In business, management is crucial for converting raw operational data into actionable information. Management helps in organizing and structuring data, making it easier to analyze and derive insights. For example, in retail, management can transform sales data from various stores into comprehensive reports showing trends, popular products, and customer preferences. This information can then be used to make strategic decisions, such as optimizing inventory levels or launching targeted marketing campaigns.In my role within the organization, data plays a significant role in decision-making and strategy development. By utilizing data analysis tools like descriptive, predictive, and prescriptive analytics, we can extract valuable insights from raw operational data. These insights help us understand past performance, predict future trends, and make informed decisions to enhance our operations and achieve our goals. Collaborating with data analysts can further improve performance by leveraging their expertise in data interpretation, modeling, and visualization to drive more informed and data-driven decisions across the organization.
2)Data analytics is a focus on techniques used to analyze data, and focus on trends and patterns. Data analytics is heavily used when organizations are making critical business decisions. In contrast, statistics focuses on collecting, studying, presenting, and organizing different types of data. Statistics focuses on the data behind data analytics. Descriptive analytics focuses on summarizing data and to help understand what happened. Predictive analytics is the focus on what may happen and future outcomes. And prescriptive analytics helps to make recommendations. Simulations models are used to help achieve organizational desired outcomes. A retail company may use data analysis to determine where sales are progressing or struggling. When descriptive analytics is used in this instance, it gives management a better breakdown of where and what items are lacking or are performing above others. In my career as a property manager, we use predictive analytics to determine where and when a rental property where fill vacancies and how rent needs to be determined for different types of property.