Power BI offers some useful AI integrations available with Azure Machine Learning and Cognitive Services that support the creation of powerful analytics dashboards.
Azure Machine Learning pre-built AI models and services easily integrated into Power BI:
- Text Analytics: Extracts key phrases, detects sentiment, and identifies languages in text data. For example, you could analyze customer reviews to identify whether they are positive or negative and the main themes. This would be extremely helpful to businesses in understanding their customers’ feedback better and implementing improvements.
- Anomaly Detection: Identifies unusual patterns in the data that may indicate problems, such as spikes or dips in sales. Let’s assume you are a store manager, and you notice a sudden decrease in sales for a particular product. By using anomaly detection, you can quickly identify and fix the cause, thereby preventing further losses.
- Image Analysis: Recognizes objects, text, faces, and emotions in images. This can be useful for retailers who want to understand customer demographics and preferences, helping them make more informed decisions on product offerings and promotions.
- Language Understanding (LUIS): Understands user intents and extracts entities from natural language text. Imagine you manage a call center and want to analyze text transcripts of calls to understand common customer issues. LUIS can identify key phrases and categorize them into specific problem areas, allowing you to address these issues effectively.
Integrate Azure Cognitive Services with Power BI to create custom visualizations:
- Prepare your data: Before you start connecting Power BI to Azure Cognitive Services, you need to clean and prepare your data. Make sure the data is in a format that can be easily ingested by Azure Cognitive Services, such as CSV, JSON, or Excel files.
- Set up a Cognitive Services resource in Azure: To access the pre-built AI models, you’ll need to sign up for an Azure account and create a new Cognitive Services resource. Once you’ve created the resource, you’ll receive an API key, which will be used to connect Power BI to the service.
- Connect Power BI to Azure Cognitive Services: Go to the ‘Home’ tab and click on the ‘Edit Queries’ button in Power BI. In the ‘Power Query’ window, click on the ‘Advanced Editor’ button. Here, you can write a custom function to call the Cognitive Services API using the API key obtained earlier. Save the function and apply it to your data.
- Perform AI-driven analysis: With the Cognitive Services API integrated into Power BI, you can now perform advanced AI-driven analysis on your data. For example, you could use Text Analytics to categorize customer reviews by sentiment or create visualizations to track anomaly detection results over time.
- Customize your dashboard: As you refine your analysis, you can create and customize visualizations and reports in Power BI to present your findings in a compelling way. Take advantage of Power BI’s wide range of visualizations, such as bar charts, pie charts, maps, and more, to effectively communicate insights.
In summary, Azure Machine Learning and Cognitive Services provide a powerful set of tools that, when combined with Power BI, allowing you to perform advanced data analytics to gain valuable insights for your business. Empower your decision-making with AI-driven analytics and create stunning dashboards to share with your team.