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Key Tools in Power BI for Predictive Analytics:
Data Preparation and Cleaning
Before building a predictive model, it essential to have clean, organized data. Power BI Data Analysts spend a significant amount of time preparing the data through Power Query, where they can filter, transform, and clean data sources to remove inconsistencies or inaccuracies. Clean data enhances model accuracy and reliability.
Steps in Data Preparation:
Feature Engineering: Creating new variables that add predictive power to the model.
By ensuring high data quality, Microsoft Power BI Data Analysts can produce more reliable predictive models that yield actionable insights.