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In the modern era of data-driven decision-making, businessintelligence projects have become the cornerstone for organizations aiming to harness their data for strategic insights. There are perhaps thousands of different approaches to the analysis of data, each with the potential to create new businessintelligence projects.
This raw data often goes through a number of transformation steps: clean and prepare, apply business rules, feature engineering, classification, scoring, and so on. . Aggregated results are then pulled into a data warehouse , or semantic layer, where business users can interact with the data using businessintelligence tools. .
This raw data often goes through a number of transformation steps: clean and prepare, apply business rules, feature engineering, classification, scoring, and so on. . Aggregated results are then pulled into a data warehouse , or semantic layer, where business users can interact with the data using businessintelligence tools. .
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