Descriptive analytics can be defined as the most common, fundamental form of business analytics used to monitor trends and keep track of operational performance by summarizing and highlighting patterns in the past and existing data.

Descriptive analytics can be applied to a wide variety of everyday operational activities of a business. Reports on inventory, various workflows, sales figures, and revenue statistics are all based on descriptive analytics. Together, these reports offer a company a historical overview of its operations.

Descriptive analytics is the first step in the analytics method process, and it provides the foundation for more advanced analytics, such as predictive analytics, and prescriptive analytics.

Some common descriptive analytics techniques include:

• Data mining: This involves using statistical and machine learning algorithms to identify patterns and trends in data.
• Data visualization: This involves using charts, graphs, and other visual representations to make data easier to understand.
• Reporting: This involves generating reports that summarize the findings of descriptive analytics.

Businesses of all sizes and sectors can benefit from descriptive analytics. It can assist firms in better understanding their customers, goods, and processes. This data can then be used to make better marketing, sales, product development, and operational decisions.

So, Descriptive analytics is a strong method for gaining insights from data. Businesses can make better decisions regarding the future if they understand what has happened in the past.