Data Science continues to evolve as one of the most promising, in-demand aspect necessary for companies to adopt. As technology advances, data science keeps on developing, prompting organization to subscribe to new innovative methods, strategies, programs and systems in order to be abreast with any changes experienced.
The types of data analytics each company needs to embrace are;
Descriptive analytics answers the question of what happened. For example, a nurse or a doctor needs to know how many patients were hospitalized last month; and a manufacturer – a rate of the products returned for a past month.
At this stage, historical data can be measured against other data to answer the question of why something happened. Companies go for diagnostic analytics as it gives in-depth insights into a particular problem. At the same time, a company should have detailed information at their disposal otherwise data collection may turn out to be individual for every issue and time-consuming.
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Predictive analytics tells what is likely to happen. It largely depend on the findings of descriptive and diagnostic analytics to figure out tendencies, exceptions, and to predict future trends, facilitating forecasting.
The purpose of prescriptive analytics is to literally prescribe what action to take to eliminate a future problem or take full advantage of a promising trend.