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Prominent Aspects To Know Before Developing A Data Science Model
Data Science has the potential to provide enterprises across industry verticals with better quality and quantity of data and information in real-time. This information that is extracted from the data can be used to accurate decisions & to analyze the market trends, to predict the changes in customer preferences and more. It is also important for companies to use data in decision making, which can help them make better business decisions and improve their overall customer service.
Data scientists are also responsible for using statistical techniques in order to predict the future trends. This is done by using mathematical algorithms such as mathematical statistics and other mathematical techniques which have proven accuracy and reliability. These algorithms are known as Bayesian statistics.
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Use Of Data Science Models in Business:
Models are useful in helping businesses in predicting their future needs and how they should be improved and changed. Some models are used to help in analyzing the profitability of a certain business, or the market. Models are also used in forecasting the future growth of a particular industry.
Prominent Aspects To Know Before Developing A Data Science Model:
- Data Scientists need to have a clear idea of the business problem for which they are going to find the solution & the KPIs associated with the business problem.
- A flowchart should be developed that includes internal business processes and external factors that may influence the KPIs associated with the problem which Data Scientists are handling
- Extracting relevant data analyzing which Data Scientists can find accurate solutions to the problem
- Define the techniques that help in the development of business model base on the KPIs.
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