Difference between business intelligence and predictive analytics

Business intelligence (BI) and predictive analytics are two distinct approaches to handle, categorize, and understand data. While BI involves transforming data into actionable insights to influence strategic business decisions, predictive analytics utilizes statistical techniques to analyze historical and current data to make predictions about future events. In other words, BI serves the purpose of gaining historical data for reporting purposes, and predictive analytics assists in forecasting to solve business environment problems.

BI analysis relies on specific metrics focused on past business performance, while predictive analytics utilizes raw data patterns that may be more challenging to detect. The analysis process for BI is based on reporting models that pull company-related data to evaluate past performances, while predictive analytics drills down to obtain necessary data using statistical, quantitative data, and algorithms. By adopting a blend of BI and predictive analytics, businesses can efficiently enhance productivity and deliver products at the right time to influence better decision-making processes.

Overall, the use of BI and predictive analytics can bring additional value to your business objectives. Informed data visualization and predictive analytics are essential tools for effective decision-making in today's data-driven world.

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