Data analytics entails employing techniques and tools on data, to extract key trends and patters critical in generating insights that can be used to make decisions. The main goal of data analytics is to handle particular issues or questions affecting a particular organization so as come up with better business outcomes. It is critical to make data-informed strategic decisions in the modern-day business environment. The significance of leveraging data lies in its ability to generate key benefits to any particular business enterprise.

Types of Data Analytics

Descriptive Analytics: This kind of analysis looks at what has happened in the past in a simple way. The analyst summarizes and organizes data to describe the current situation. Such analysis utilizes measures such as standard deviation, mean, median, and mode to bring out the main characteristics of a data set. The analyst then presents the data in a way that can be understood by a majority of people.

Diagnostic Analytics: In this type, analysts look a particular dataset to gain insights into why something happened. Such involves looking at anomalies in the dataset, and investigate the reasons behind such anomalies. Analysts do so with help of additional data sources that assist in uncovering such anomalies.

Predictive Analytics: This kind of analysis looks at what is likely to happen in the future. Data analysts apply statistical techniques on historical data to forecast future outcomes. With the help of machine learning algorithms and probability theory, key outcomes can be forecasted for instance a company’s revenue at a certain time or the probability of a certain product to hit a given revenue at a particular time.

Prescriptive Analytics: Prescriptive analysis suggests the course of action to be taken based on the insights generated from diagnostic and predictive analysis. Data analysts look at a wide range of possible scenarios and examine the various approaches the organization can take. This type of analysis may necessitate the use of computational modelling and machine learning algorithms.