Amazon Q Business: Your First Hands-On Demo
- Sesha Sravani Ch
- Oct 9
- 3 min read
Amazon Q is Amazon’s Generative AI assistant designed for business users, developers, and customer service teams. As a cloud-based SaaS service hosted on AWS, it allows you to securely analyze data, generate insights, and improve workflows, all without managing servers or writing complex code. You access it directly through your AWS account, upload your data, and ask natural language queries to get results instantly.
Amazon Q comes in three forms:
Amazon Q Business: Access and analyze company data securely.
Amazon Q Developer: Helps with code generation, debugging, and IDE integration.
Amazon Q in Connect: Supports customer service agents and improves customer interactions.
In today’s fast-paced business world, making sense of data quickly is critical. Amazon Q Business is a generative AI tool that helps business users, analysts, and customer service teams analyze data, generate insights, and make informed decisions, all without writing code.
In this blog, we shall focus on creating an Amazon Q Business application, uploading data, and using its Web Experience to run queries and get instant insights
Step 1: Start Creating Your Application
Log in to your AWS account and choose Amazon Q from AWS services.
Click Get Started to create a new Amazon Q Business application.
Application Name: Enter a descriptive name, e.g., Sales-Demo-App.
Step 2: Choose User Access
Select Anonymous Access.
This allows anyone to access the application without authentication.
Choosing this makes it easier to test and explore without setting up IAM Identity Center.
Features that require authentication will not be available.
Leave the rest of the options at their default values and click Create.
Following are the screenshots attached, showing the above mentioned steps.
Step 3: Create the Application
Scroll down and click Create.
AWS will set up your Sales-Demo-App and take you to the application dashboard.
Upload Your First Data Source
Amazon Q Business works with structured data files like CSV or Excel spreadsheets. Before uploading your file, you’ll need to create an index, which organizes your data and makes it queryable. Here’s an example of a simple sales dataset one can use for this demo:
Click Data Sources
Since the index is not yet created, Add data source button is disabled.(See the below screen shot)
Click Add an index --> Give an index name -->Select Index provisioning : Starter
Click Add an index . Amazon Q will set up the index.
Once the index is ready, the Add Data Source button becomes active, and the CSV file can be uploaded. The index then organizes your file so Amazon Q can quickly search and answer queries.
Think of the index as a preparation step, it tells Amazon Q how to look at your data efficiently.
AWS manages the technical setup behind the scenes, but you still have to create the index and connect your file.
Step 4: Connect your data source to the index
After creating your index, click Add Data Source --> Upload File .
Select the file you want to use and click Upload. You can see salesdemo.csv attached in the screenshot .
Amazon Q will process the file and associate it with the index you created.
Click Done
Step 5: Open the Web Experience
In your application dashboard, Click Preview Web Experience
This opens a chat-style interface where you can interact with Amazon Q using natural language.
Example queries for the sales data set:
Show total sales by month.
Who are the top 2 customers?
Which region performed best in February?
Amazon Q will return tables, charts, or summaries, depending on the query.
There you have your Amazon Q Business catering to your needs :)
Amazon Q Business brings the power of AI-driven insights to your fingertips. By simply uploading your data and asking questions in natural language, you can uncover trends, make decisions faster, and explore your business metrics effortlessly.
With minimal setup and no coding required, it’s a practical tool for anyone looking to turn data into actionable insights quickly and securely.
Beyond analyzing business data, Amazon Q also supports developers and customer service teams. For developers, it can generate unit test cases, assist with debugging, and explain complex code in plain language, making coding faster and more reliable. For customer service teams, Amazon Q in Connect integrates directly into contact centers, helping agents respond faster with AI-generated suggestions, knowledge base lookups, and contextual insights. For example, when a customer calls about a billing issue, Amazon Q in Connect can automatically surface the relevant account details and recommend the best response, allowing the agent to resolve the query quickly. Together, these capabilities show that Amazon Q is not just a business analytics tool but a complete AI assistant that adapts to multiple use cases across an organization.
