6 AI Features in Power BI Every Data Analyst Should Use 🧵🧵
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1. Sentiment Analysis with Power BI
When next you are analyzing SUrvey data with Power BI, you should use this feature to perform sentiment analysis.
The output will help you get more insight and do a better job
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When next you are analyzing SUrvey data with Power BI, you should use this feature to perform sentiment analysis.
The output will help you get more insight and do a better job
#PowerBI
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2. Ask Questions with Natural Language
Curiosity is part of a Data Analyst skill. This feature is timely for doing some deep dive when you are trying to explain some WHYs in your report.
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Curiosity is part of a Data Analyst skill. This feature is timely for doing some deep dive when you are trying to explain some WHYs in your report.
#PowerBI
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3. Smart Data Discovery and Visualization
This feature can come in handy in many scenarios. It automatically builds a Power BI report on top of your data which can further be customized.
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This feature can come in handy in many scenarios. It automatically builds a Power BI report on top of your data which can further be customized.
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4. Anomaly Detection
Anomaly detection can be used to detect fraudulent activities in transactions as it helps you spot hidden patterns.
See a use case below
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Anomaly detection can be used to detect fraudulent activities in transactions as it helps you spot hidden patterns.
See a use case below
#PowerBI
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5. Key Influencers Visual
This visual provides you insight to understand the factors that drive the metrics you are interested in.
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This visual provides you insight to understand the factors that drive the metrics you are interested in.
#PowerBI
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6. Root Cause Analysis in Power BI
Using the decomposition tree visual, you can perform deeper Root Cause Analysis influenced by AI.
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Using the decomposition tree visual, you can perform deeper Root Cause Analysis influenced by AI.
#PowerBI
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