Data analysis refers to the comprehensive process of obtaining useful data and analysing it in order to make more reliable decision-making processes for a business or for the goal of an organisation. The process begins with gathering information and progresses to interpreting, analysing, and finally acting on it. There are various methods for analysing data in order to make an informed business decision. Each type of analysis has a distinct goal and methodology.
It is divided into four categories:
- Descriptive analytics is a method that focuses on numerical data. It answers the question, “What happened?” For example, the average number of articles written per employee per month, a poll of users’ favourite articles, or the average number of likes per post.
- Diagnostic analytics: This method of analysis goes beyond descriptive analysis to answer the question “why?” It also aids in determining the cause of a negative or positive outcome.
- Predictive Analytics: This type of analysis allows you to use data to forecast your future. As the name implies, you will forecast future tendencies and trends based on the data you collect to answer the question.
- Prescriptive Analytics: This type of analysis focuses on acting strategically for your business decisions, which are supported by statistical data, clear facts, and visual data. This type of analysis should not be based on observation or intuition. It differs from predictive analysis in that it requires actionable methodologies and machine learning to achieve a conclusive insight. Instead of a prediction, statistical algorithms are required.
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