Building KPI dashboards using Redshift and QuickSight

 In the data-driven world of modern business, KPI (Key Performance Indicator) dashboards play a crucial role in monitoring performance, tracking progress, and enabling quick decision-making. When you combine Amazon Redshift (a powerful cloud data warehouse) with Amazon QuickSight (a scalable BI service), you can build dynamic, interactive dashboards that provide real-time visibility into your organization’s KPIs.

In this blog, we’ll walk you through the process of building a KPI dashboard using Redshift and QuickSight.


🛠️ Prepare Your Data in Amazon Redshift

Redshift is optimized for large-scale data analytics. Before building dashboards, make sure your data is structured and loaded properly.

Tasks to do:

Design star or snowflake schema for reporting

Load data using ETL tools (AWS Glue, DMS, or custom Python scripts)

Use SQL to create aggregated views or materialized views for KPIs (e.g., revenue, user growth, churn rate)

Example SQL for Monthly Revenue:

CREATE VIEW monthly_revenue AS

SELECT 

  DATE_TRUNC('month', order_date) AS month,

  SUM(order_amount) AS total_revenue

FROM sales_data

GROUP BY 1

ORDER BY 1;

📊  Connect Redshift to Amazon QuickSight

QuickSight makes it easy to create visualizations directly from Redshift.

Steps:

Go to Amazon QuickSight

Choose Manage data → New dataset

Select Redshift as the data source and provide:

Cluster details

Database name

Credentials

Choose the tables or views (like monthly_revenue) to import or use with Direct Query


📈  Build KPI Visuals

After importing the data:

Use the Analysis tab in QuickSight

Add KPI widgets like:

Revenue (Total/Monthly/Yearly)

Active Users

Conversion Rates

Churn Rate

Use filters, parameters, and controls for user interaction (like region or date range filters)

Apply conditional formatting to highlight critical values (e.g., negative growth in red)


🔄  Automate and Schedule Updates

Set data refresh schedules (hourly, daily, weekly) for real-time accuracy

Use SPICE (Super-fast, Parallel, In-memory Calculation Engine) for faster performance if importing data


🔒  Share and Secure

Share dashboards with stakeholders using QuickSight’s built-in access controls

Set row-level security (RLS) to restrict data visibility by role or department

Embed dashboards into internal apps or portals using QuickSight Embedding SDK


✅ Benefits of This Integration

  • Scalability: Handle petabyte-scale data in Redshift
  • Speed: SPICE accelerates performance
  • Interactivity: Drill-downs, filters, and visuals help analyze KPIs deeply
  • Security: AWS-native security and IAM integration


🧠 Final Thoughts

By integrating Redshift with QuickSight, you enable a powerful data analytics pipeline that transforms raw data into actionable insights. Whether you're tracking financial health, product performance, or customer behavior, KPI dashboards built on these AWS tools help your business stay agile, data-informed, and competitive.

Learn AWS Data Engineer Training

Read More: Deploying Spark applications using AWS EMR Serverless

Read More: Applying data masking in Redshift views

Read More: Leveraging IAM roles for secure data access


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