Power BI Copilot | Prep Data for AI, Create Reports & Ask Questions

Summary

This video explores the capabilities of Power BI's Copilot, focusing on how it helps users prepare data for AI, automate query generation, and streamline reporting. Key features include simplifying data schemas, adding AI instructions for improved context, and using verified answers for consistency. Copilot can also generate and explain DAX queries, helping users navigate complex formulas. While not a complete replacement for human expertise in data visualization, Copilot serves as a valuable starting point, especially for beginners. The video encourages users to try Copilot and share their experiences to enhance its functionality.

Takeaways

• 😀 Simplify your data schema to remove irrelevant tables and columns, making your data model easier for CoPilot to understand.
• 😀 Ensure your data security measures are intact when prepping data for AI, so users only see relevant information.
• 😀 Use verified answers in Power BI to provide clarity for CoPilot and ensure accurate responses when querying data.
• 😀 Add context and industry-specific terms to CoPilot’s instructions to help it better interpret your data and improve query results.
• 😀 CoPilot can generate DAX queries, like profit by country over the last 6 months, with just a simple command, saving you time.
• 😀 If you’re unsure about a generated DAX query, CoPilot can explain it in simpler terms, helping you understand complex queries.
• 😀 CoPilot helps break down complex DAX code into digestible summaries, which can be useful for reviewing or explaining your queries.
• 😀 Power BI’s AI features can inspire report creation, especially for beginners who might be unsure how to get started.
• 😀 Despite the advancements, CoPilot won’t fully replace human analysts yet, as it doesn’t offer the same level of visualization and targeted reporting.
• 😀 Starting with Power BI’s standalone experience and gradually progressing to desktop and CoPilot can help ease into the tool, even for beginners.
• 😀 CoPilot in Power BI offers great potential for automation and data analysis, but it still requires user input and verification to generate meaningful results.

Q & A

What is the main purpose of using AI-powered features in Power BI as mentioned in the video?

The main purpose is to streamline data analysis and report generation by using Copilot, which assists with data preparation, query creation, and simplifying the visualization process, allowing users to focus on insights rather than manual data handling.

How can users simplify the data schema in Power BI when preparing data for Copilot?

Users can simplify the data schema by unselecting irrelevant tables, columns, or measures that are not essential for the analysis. This ensures that Copilot only processes relevant data and avoids clutter from unnecessary data elements.

What is the significance of 'Verified Answers' in Power BI with Copilot?

Verified Answers in Power BI allow users to pre-define common queries or business-related phrases, which helps Copilot understand specific terminologies or expected results, leading to more accurate and context-aware responses during analysis.

What kind of information can be included in the 'AI Instructions' field to improve Copilot’s performance?

Users can include context about important data fields, business goals, industry-specific terms, and any complex logic like if-then-else statements to improve Copilot’s understanding of the data and generate more relevant outputs.

What is the role of DAX query generation in Power BI with Copilot?

DAX query generation in Power BI with Copilot allows users to request complex queries (like profit by country for the last 6 months) and have Copilot automatically generate the DAX code. Users can then fine-tune, save, and run these queries in their reports.

How does Copilot help explain complex DAX queries in Power BI?

Copilot can summarize and explain complex DAX queries by providing a plain-language breakdown of the query logic, what the query is doing, and what the expected output will be. This helps users, especially those new to DAX, understand the query's purpose and results.

What happens when a user opts to update their data model with changes made through Copilot?

When a user updates their data model with changes made through Copilot, such as adding a new DAX measure, the changes are reflected in the Power BI model, and the user can see these updates in their reports and dashboards.

Why is it important to provide as much context as possible when interacting with Copilot in Power BI?

Providing more context helps Copilot better understand the business rules and data nuances, leading to more accurate and relevant outputs. Just like communicating with a person, clear and detailed information enables Copilot to give better responses and insights.

What is the benefit of using Power BI's standalone experience and desktop experience for new users?

The standalone and desktop experiences in Power BI allow new users to experiment with different features, see how reports are generated, and understand the capabilities of Copilot. It serves as a good starting point to explore the tool and build confidence before diving into more complex workflows.

What is the speaker’s opinion on the current capabilities of Copilot in Power BI?

The speaker is generally positive about Copilot's potential, seeing it as a useful tool for automating report generation and inspiring users, especially those new to Power BI. However, they note that it is not yet a full replacement for human expertise, particularly in visualizing data effectively.