Creating dynamic dashboards in QuickSight from Athena

In today’s data-driven world, the ability to visualize large-scale datasets quickly and effectively is a competitive advantage. Amazon QuickSight, a cloud-native business intelligence (BI) service, allows you to create interactive dashboards with minimal effort. When paired with Amazon Athena—a serverless, pay-per-query analytics service—you can query data directly from Amazon S3 and visualize it instantly in QuickSight.

This blog walks you through how to create dynamic dashboards in QuickSight using Athena as your data source, empowering you to deliver fast, flexible, and insightful reporting solutions.


Why Use QuickSight + Athena?

  • Combining QuickSight with Athena enables you to:
  • Query massive datasets stored in Amazon S3 without data movement.
  • Eliminate the need for complex ETL pipelines.
  • Build interactive, real-time dashboards from raw or processed data.
  • Pay only for the queries you run and the dashboard usage.


This setup is ideal for modern data lakes, event-driven architectures, and serverless analytics workflows.

Step 1: Prepare Your Data in Amazon S3

Ensure your data is:

  • Stored in a supported format (e.g., CSV, JSON, ORC, Parquet).
  • Partitioned efficiently if you're working with large datasets.
  • Properly structured (consistent schema, clean column names, etc.)
  • You don’t need to move your data anywhere—Athena can query it directly from S3.


Step 2: Create Tables in Athena

Go to the Athena console and select your database (or create a new one).

Run a CREATE EXTERNAL TABLE statement or use the Glue Data Catalog to define metadata.


sql

Copy

Edit

CREATE EXTERNAL TABLE IF NOT EXISTS sales_data (

    order_id string,

    customer_name string,

    region string,

    total_amount double,

    order_date string

)

ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe'

WITH SERDEPROPERTIES (

  'serialization.format' = ','

)

LOCATION 's3://your-bucket/sales/'

Use SELECT statements to preview and validate the data.


Step 3: Connect QuickSight to Athena

  • In the QuickSight console, go to Manage Data > New Dataset.
  • Choose Athena as the data source.
  • Provide a name and connect using the AWS Glue Data Catalog.
  • Choose your database and table, then import or use SPICE for in-memory performance.


Step 4: Create a Dynamic Dashboard

Use QuickSight’s drag-and-drop interface to add visualizations:

  • Bar charts for sales by region
  • Time series for revenue trends
  • Heatmaps for performance metrics
  • Add filters, parameters, and controls to allow users to:
  • Filter by date ranges
  • Choose specific regions or products
  • Drill down into granular data

Use calculated fields to derive custom metrics (e.g., profit margin, YoY growth).


Step 5: Share and Schedule Dashboards

  • Share dashboards with specific users or groups.
  • Set up scheduled email reports.
  • Embed dashboards into internal apps or portals using the QuickSight API.


Best Practices

  • Use SPICE for performance when visualizing frequently queried data.
  • Apply row-level security (RLS) to restrict access by user role or region.
  • Optimize Athena queries with proper partitioning and file formats like Parquet.


Conclusion

With QuickSight and Athena, you can go from raw S3 data to rich, interactive dashboards in just a few steps. This serverless, scalable combo eliminates the need for heavy infrastructure and makes analytics accessible across your organization. Whether you’re building executive dashboards or self-service reporting tools, this integration can deliver real-time insights with minimal overhead.

Learn AWS Data Engineer with Data Analytics

Read More: Real-time error notification for failed Glue jobs

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