How can we use AI in PowerBI. 

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AI capabilities in Power BI empower users to delve deeper into their data, make better-informed decisions, and streamline tasks within their reports and dashboards. 

Here are several ways AI can be utilized in Power BI:

Natural Language Query (Q&A): Users can pose questions about their data in natural language through the Q&A feature. Power BI employs AI algorithms to comprehend the query and produce visualizations or reports from the data.

AI Visualizations: Power BI provides AI-driven visualizations like Key Influencers and Decomposition Tree. Key Influencers pinpoint the factors that most affect a target metric, and the Decomposition Tree enables users to explore the elements contributing to a particular value.

Anomaly Detection: Power BI's AI features can identify data anomalies, aiding users in spotting unusual patterns or outliers that warrant additional scrutiny. This is especially valuable for spotting irregularities in time-series data, such as unexpected surges or drops in sales figures.

Automated Insights: Power BI can autonomously generate insights and explanations from data, accentuating trends, correlations, and anomalies. Users can utilize these insights for a better understanding of their data and to inform their decisions.

Data Preparation: AI aids in data preparation by automatically identifying and rectifying data discrepancies, gaps, or anomalies. Power BI's AI tools enable users to cleanse and modify data more effectively, conserving time and resources.

Predictive Analytics: Power BI facilitates the integration of machine learning models for predictive analytics. Users can develop and implement machine learning models within Power BI to project future patterns, anticipate outcomes, or categorize data.

Personalized Recommendations: AI-driven recommendations in Power BI offer pertinent content, insights, or actions based on user activity, behavioral patterns, and data examination. This assists users in uncovering new insights and taking more effective actions. 

Data Insights in Excel: Power BI's integration allows users to access AI-driven insights directly in Excel. This feature enables the application of AI tools such as data profiling, outlier detection, and trend analysis within Excel workbooks.

Text Analytics: Power BI provides text analytics capabilities for unstructured data like customer feedback, social media posts, or survey responses. It employs AI algorithms to extract key insights, conduct sentiment analysis, and perform topic modeling for enhanced visualization and analysis.

Automated Machine Learning (AutoML): The collaboration between Power BI and Azure Machine Learning supports automated machine learning workflows. This enables users to effortlessly create, train, and deploy machine learning models within Power BI, without any coding requirement.

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