Data analysis is an essential aspect of managing an effective organisation. Whenever data is used efficiently, it leads to a greater knowledge of a company’s past performance and more informed decisions about its future operations. Data can be utilised in a variety of ways at all stages of an operation of the company.
5 types of Data Analytics
Data analytics can be broadly divided into five types. It is crucial to understand that no specific type of analytics is superior to another. In fact, they coexist and enhance one another.
To better comprehend what is happening or what has happened, descriptive analytics describes or summarises the existing data utilising current business intelligence technologies. Standard reports, customer behaviour, customer profitability, historical rival activity, monthly profit and loss statements, and demographic data are examples of descriptive analytics.
Focus on prior performance to ascertain what transpired and why. An analytical dashboard is frequently the outcome of the analysis. This kind of analytics often aims to go further into a certain cause or set of hypotheses based on the descriptive analytics. Diagnostic analytics delve deeply, looking into the costs of problems, whereas descriptive analytics cast a wide net to comprehend the breadth of the data.
Predictive analytics transforms the data into useful and practical knowledge. Predictive analytics utilises data to estimate the chance of a condition arising or the likely course of an occurrence. In order to anticipate future events, predictive analytics uses a number of statistical approaches from modelling, machine learning, data mining, and game theory. These techniques evaluate both current and past data.
One of the three primary forms of analytics used by businesses to evaluate data is prescriptive analytics, alongside descriptive and predictive analytics. Although this sort of analytics is frequently referred to as a form of predictive analytics, its emphasis is slightly different.
It combines a number of clever technologies, including deep learning models, machine learning algorithms, and artificial intelligence to simulate the human brain and provide results that are similar to how people think.