As, data mining and analyzing information to drive conclusion and sense from that data is an elaborate task. Data analytics (descriptive statistics) can be done in three types predictive, descriptive, and prescriptive. Descriptive analytics describes the past by using data aggression and data mining techniques to derive insights from the past data. Nowadays, as the quantity of data is increasing enormously using these techniques to analyze it is justified. according to Transparency Market Research, the global descriptive analytics market is anticipated to rise at a healthy CAGR during the forecast period between 2016 and 2024.
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Why there is a Need for Descriptive Analytics?
Descriptive analytics can summarize samples and observations that have been made in past in form of visual or quantities. The data can be a part of widespread statistical analysis. This is the basis of the primary description of the data or is sufficient in themselves to take forward a particular investigation. It can also be called post-mortem analysis. Descriptive analytics is used for nearly for all management reporting, such as sales, finance, marketing, and operations.
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Post-mortem analysis is used for almost all management reporting, such as marketing, operations, sales, and finance. To sustain the position in the market, companies use advanced analytics, which also supports them in predicting trends in coming years. The forecasting allows companies to make improved decisions that has further expanded the profitability for this market. Moreover, growing analytics and increasing rate of investments need descriptive analytics thus flourishing the demand in this market.
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Data analytics is highly used in healthcare sector as it gives in creating risk scores for chronic diseases and can help patients to avoid long-term health problems. It also helps in improving transitions of care and deploying care coordination strategies, and informs the patient is there is a risk for readmission within the 30-day period.