what is classification of analytics with explain and their advantages in pointwise.

Classification of analytics refers to the grouping of various analytical techniques based on their purpose or function. These classifications help to differentiate and understand the different types of analytics and their applications. The most common classifications of analytics are descriptive, diagnostic, predictive, and prescriptive analytics. 1. Descriptive Analytics: Descriptive analytics is concerned with summarizing and presenting historical data in a meaningful way. It helps to answer questions such as what happened, when, where, and how. This type of analytics provides valuable insights into past performance, trends, and patterns, which can be used to understand the current state of affairs. The advantage of descriptive analytics is that it is relatively easy to implement and provides a good starting point for further analysis. 2. Diagnostic Analytics: Diagnostic analytics is a more advanced form of descriptive analytics that helps to identify the root cause of a problem or a situation. It uses statistical and data mining techniques to analyze historical data and uncover trends, patterns, and relationships. By understanding the reasons behind past events, organizations can make informed decisions and take corrective actions to improve future outcomes. The advantage of diagnostic analytics is that it helps to identify the cause of an issue, which is crucial for problem-solving and decision-making. 3. Predictive Analytics: Predictive analytics uses statistical models and machine learning algorithms to analyze historical data and make predictions about future events or trends. It helps to answer questions such as what is likely to happen, why it will happen, and what can be done about it. Predictive analytics is used in various industries, such as finance, marketing, and healthcare, to forecast customer behavior, market trends, and equipment failure. The advantage of predictive analytics is that it helps organizations to anticipate potential outcomes and make proactive decisions. 4. Prescriptive Analytics: Prescriptive analytics is the most advanced form of analytics that combines insights from descriptive, diagnostic, and predictive analytics to recommend the best course of action to achieve a specific goal. It uses algorithms and simulation techniques to evaluate various scenarios and identify the most optimal solution. Prescriptive analytics is used in complex decision-making processes, such as supply chain optimization, inventory management, and resource allocation. The advantage of prescriptive analytics is that it can help organizations to make more informed decisions, improve efficiency and reduce costs. In conclusion, each type of analytics has its advantages and plays a crucial role in the decision-making process. By understanding the different classifications of analytics, organizations can choose the most relevant type for their specific needs and make better use of their data to drive business growth and success.