DATABRICKS AI/BI GENIE | No Code Interface For Your Data | Text TO SQL

Introduction

Introduction

Welcome back! In this article, we are focusing on Databricks AI/BI Genie (often simply referred to as "Genie"), a no-code, low-code solution designed to simplify data querying through natural language interaction. This innovative tool behaves similarly to a text-to-SQL interface, allowing users to ask questions in natural language, which are then converted into SQL queries, fetching answers from the database in a digestible format.

Enabling AI/BI Genie in Databricks Workspace

To start utilizing Genie in your Databricks workspace, you need administrative rights. Notably, this feature is not available in the free version of Databricks; you must utilize either the free trial or a paid version. Follow these steps to enable Genie:

1. Navigate to the Previews section within your Databricks console.
2. Locate the Genie feature and toggle it on.
3. Refresh your page to see the Genie option appear in your user interface.

Once activated, you can start creating a “space” where users can interact with their data.

Creating and Exploring a Space

To create a space where data queries can be executed, perform the following:

1. Click the plus icon to create a new space.
2. Provide a title and description of the data available in this space.
3. Select a SQL warehouse for querying, ensuring it's either a paid or serverless version.
4. Choose the tables to be added to this space, which will serve to answer user queries.

It's advisable to start with a small scope in the space's dataset for effective management and governance.

Making Genie Smarter Over Time

Genie improves its accuracy and relevance by learning from user interactions. Here’s how you can enhance its performance over time:

• Feedback Mechanism: Provide feedback by giving thumbs up to responses you find helpful.
• Add Instructions: You can add specific instructions for how you’d like the AI assistant to behave or learn.

This can be done directly in the Genie interface where it maintains a record of previous instructions and suggestions.

Best Practices for Enhancing AI Performance

Follow these best practices to make the most out of Genie:

• Include Detailed Descriptions: Always provide descriptions for data tables. This helps Genie provide more accurate responses.
• Add Comments: Ensure each column in your datasets has comments explaining their purpose. This context allows the AI to draw more intelligent conclusions during queries.

Conclusion

Using Genie within Databricks enables users—especially business analysts and data professionals—to extract insights without needing deep SQL knowledge. The integration of natural language querying into database interactions streamlines the data analysis process and empowers users to leverage data effectively.

In the upcoming article, we will delve into how to integrate AI capabilities into Databricks dashboards, further enhancing your data visualization experience. Thank you for reading, and stay tuned!

Keywords

• Databricks
• AI/BI Genie
• No-Code Interface
• Text to SQL
• SQL Warehouse
• Data Querying
• Natural Language Processing
• Data Visualization
• User Interface
• Best Practices

FAQ

1. What is Databricks AI/BI Genie?
Databricks AI/BI Genie is a no-code, low-code solution that allows users to query databases using natural language, converting those queries into SQL and providing answers in an easy-to-understand format.

2. Do I need to be an admin to enable Genie?
Yes, you need administrative rights to enable the Genie feature within your Databricks workspace.

3. Can I use Genie with the free version of Databricks?
No, Genie is not available in the free version. You must use either the free trial or a paid version of Databricks.

4. How does Genie learn over time?
Genie utilizes user interactions to improve its accuracy and relevance. Users can provide feedback and add instructions that Genie considers in future interactions.

5. What are some best practices for using Genie?
Best practices include providing detailed descriptions of tables and adding comments to dataset columns for enhanced AI performance.