Data analysis aims to compile and process data associated with a business operation, generating knowledge that can reduce uncertainty in managers' decision-making.

BI solutions feature an intuitive interface while providing advanced visual representations. They also allow for the fusion of data from diverse sources, streamlining evidence-based decision-making.

Predictive analytics is used to identify the likelihood of future outcomes based on historical data. Its purpose is to go beyond understanding what happened, seeking a more accurate assessment of future possibilities.

Performance evaluation defines criteria and goals, while data analysis provides detailed information to measure actual performance against those criteria. Together, these practices allow us to evaluate, understand, and improve business processes, making operations more efficient and adaptable to established goals.

For statistical data analysis, it is recommended to use tools that offer robust capabilities for data manipulation, transformation, and visualization. The choice should be guided by the specific project requirements, the availability of data processing resources, scalability, and the team's familiarity with the tool.

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