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Magpie Vaccine Supply Chain, 2. What type of support is provided by the…

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        Descriptive analytics is the analysis of historical data using two key methods – data aggregation and data mining - which are used to uncover trends and patterns. Descriptive analytics is not used to draw inferences or make predictions about the future from its findings; rather it is concerned with representing what has happened in the past.
        
        Descriptive analytics are often displayed using visual data representations like line, bar and pie charts and, although they give useful insights on its own, often act as a foundation for future analysis. Because descriptive analytics uses fairly simple analysis techniques, any findings should be easy for the wider business audience to understand.
        
        For this reason, descriptive analytics form the core of the everyday reporting in many businesses. Annual revenue reports are a classic example of descriptive analytics, along with other reporting such as inventory, warehousing and sales data, which can be aggregated easily and provide a clear snapshot of a company’s operations. Another widely used example is social media and Google Analytics tools, which summarise certain groupings based on simple counts of events like clicks and likes.
        
        Whilst descriptive data can be useful to quickly spot trends and patterns, the analysis has its limitations. Viewed in isolation, descriptive analytics may not give the full picture. For more insight, you need delve deeper.
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