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What is Descriptive Analytics? Definition and Examples

Descriptive analytics is crucial for businesses globally as it involves interpreting historical data to understand overall business circumstances. The rise of data and demand for data-driven decision-making has made descriptive analytics a foundation for advanced analytics. It involves finding trends, patterns, and insights to draw findings from data.

We will guide you through the basics of descriptive analytics to analyze data effectively and efficiently. It can unlock the potential of data, and improve overall business performance.

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What is Descriptive Analytics?

What is Descriptive Analytics

Descriptive analytics is a branch of data analytics that involves looking into past data to understand what has happened and find relative patterns and trends. This analytics uses graphs, charts, and reports to make it easy to analyze. This is the preliminary phase of data processing, which involves using data to describe previous events.

Descriptive analytics is the process used to answer questions such as “What happened?” and “What is happening?”.

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Examples of Descriptive Analytics

Below are a few examples of areas where descriptive analytics can be used:

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How Does Descriptive Analytics Work?

Descriptive analytics focuses on describing and analyzing historical data. By analyzing past performance, companies can identify the areas where they need to improve. This process involves using statistical methods as well as tools for examining infinite data sets and extracting valuable information.

Steps Involved in Descriptive Analytics

Here are several steps followed when conducting a descriptive analysis for a business:

To display data effectively and accurately, it is essential to carefully review both the audience and the information that needs to be presented.

Benefits of Descriptive Analytics

Descriptive analytics can benefit various organizations or individuals, such as businesses, financial analysts, marketing professionals, etc. It is because they rely on a large amount of data to make profitable choices for the company.

Below are some of the benefits of descriptive analytics:

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Descriptive vs. Predictive vs. Prescriptive Analytics

Descriptive vs. Predictive vs. Prescriptive Analytics

Among the several types of Data analytics, descriptive, predictive, and prescriptive analytics are differentiated below.

Descriptive Analytics 

Predictive Analytics

Prescriptive Analytics 


Summing up, it is to be noted that descriptive analytics is one of the most powerful tools for gaining insights into historical data and past trends in the market. Using data visualization and statistical analysis techniques, descriptive analytics can help reveal different marketing strategies, trends, and patterns that might otherwise be hidden.

Career Transition

To understand areas for improvement and customer behavior with historical data, the ability of descriptive analytics must be addressed. As data continues to be an essential part of organizations across various industries, mastering descriptive analytics has become crucial for professionals to uncover new opportunities and innovations.

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