Business Advantages of using Predictive Analytics in Power BI
Predictive analytics reports generated using Power BI presents thorough reports and valuable insights from the data, whether it is available on-premise or on the cloud. It allows businesses to forecast possible outcomes or events that might occur in the future.
Here are some advantages of using predictive analytics in Power BI
Fraud Detection: High-performance behavioral predictive analytics analyzes all behavioral patterns on a network in real-time to catch abnormalities that may indicate fraud, vulnerabilities, and advanced persistent threats.
Sales Forecasting: Realistic prediction of the demand for a product or service is necessary for a business to succeed. Predictive analytics models forecast to short-term, medium-term, or long-term forecasting. Predictive analytics anticipates customer response and changing attitudes by looking at all factors. It allows to predict the revenue and to allocate resources optimally.
Risk Reduction: Customer analytics is the dominant metric used by finance and insurance industries to understand the risk factors associated with each borrower. Predictive analytics models determine the credit score or creditworthiness of each individual. It helps banks and insurance companies to mitigate risks and make data-driven decisions.
Marketing Optimization: Marketing analytics helps in understanding customer insights using historical purchasing behaviors and patterns. It helps in determining trends in customer behavior and promoting cross-sell opportunities. Predictive systems help corporations attract, retain and grow their most profitable customers.
Decision Management: Predictive analytics leads to better and more advanced decisions. Business analytics and intelligence use as much data made available to identify patterns and trends to retrieve actionable insights that otherwise would not have been available. It leads to informed business decisions, improving the overall decision management.
Enhance Operational Efficiency: Predictive analytics helps in the effective management of supply/demand inventory and resources. Airlines use predictive models to set ticket prices over the short and long term. Hotels use predictive analytics to forecast the number of guests for any given night or season to maximize occupancy rates and increase sales revenue.