Amazon QuickSight and Amazon SageMaker Canvas: A Powerful Combination for Predictive Analytics

Amazon QuickSight and Amazon SageMaker Canvas are two robust AWS services that can be used together to enable predictive analytics for businesses of all sizes.

What is Amazon QuickSight?

Amazon QuickSight is a business intelligence service that makes it easy to analyze data and create visualizations. With QuickSight, you can create interactive dashboards and reports that help you understand your data and make better decisions.

What is Amazon SageMaker?

Amazon SageMaker Canvas is a no-code machine learning (ML) service that enables business analysts and data science teams to build their own ML models without having to write a single line of code. With SageMaker Canvas, you can build models to predict outcomes, identify trends, and optimize your business.

How does this duo work? 

‍“New capability unlocked”

Amazon QuickSight announced support for predictive analytics using Amazon SageMaker Canvas. This means that you can now use Amazon SageMaker Canvas to build and train ML models, and then use those models to generate predictions in Amazon QuickSight.

In Brief, QuickSight authors can now export data to SageMaker Canvas, build ML models, and share them back to QuickSight for consumption. This is an effective new capability that can help us make better business decisions by enabling us to see what is likely to happen in the future through a user-friendly, no-code interface, and making it accessible to a wider audience.

Use cases 

Here are some use cases of how you can use Amazon QuickSight and Amazon SageMaker Canvas to build predictive dashboards:

Predict customer churn:

Build your own predictive dashboard with Amazon QuickSight and Amazon SageMaker Canvas to identify those customers at risk of leaving the company. Such data then makes it possible to create highly personalized marketing efforts in order to keep such clients.

For example, you could build a dashboard that shows the following metrics for each customer:

• Number of days since last purchase
• Total amount spent
• Average purchase value
• Number of products purchased
• Customer satisfaction score

You could then use Amazon SageMaker Canvas to build an ML model that predicts which customers are most likely to churn based on these metrics. Once the model is trained, you can publish it back to Amazon QuickSight and use it to generate predictions for new customers.

Forecast sales:

Building a predictive dashboard with Amazon QuickSight and Amazon SageMaker Canvas that forecasts sales for the next quarter. With this information, you can make informed decisions about production and inventory levels.

For example, you could build a dashboard that shows the following metrics for each product:

• Historical sales data
• Seasonality trends
• Promotional activity
• Competitive landscape

You could then use Amazon SageMaker Canvas to build an ML model that forecasts sales for the next quarter based on these metrics. Once the model is trained, you can publish it back to Amazon QuickSight and use it to generate forecasts for new products.

Identify fraudulent transactions:

You can use Amazon QuickSight and Amazon SageMaker Canvas to build a predictive dashboard that identifies fraudulent transactions. This information can then be used to prevent fraud and protect your customers.

For example, you could build a dashboard that shows the following metrics for each transaction:

• Transaction amount
• Transaction location
• Transaction time
• Customer information
• Device information

You could then use Amazon SageMaker Canvas to build an ML model that identifies fraudulent transactions based on these metrics. Once the model is trained, you can publish it back to Amazon QuickSight and use it to generate predictions for new transactions.

Optimize marketing campaigns:

You can use Amazon QuickSight and Amazon SageMaker Canvas to build a predictive dashboard that optimizes your marketing campaigns. This information can then be used to target your marketing efforts more effectively and improve your ROI.

For example, you could build a dashboard that shows the following metrics for each customer segment:

• Click-through rate
• Conversion rate
• Customer lifetime value
• Marketing channel engagement

You could then use Amazon SageMaker Canvas to build an ML model that predicts which customers are most likely to respond to each marketing channel. Once the model is trained, you can publish it back to Amazon QuickSight and use it to optimize your marketing campaigns.

Improve operational efficiency:

Amazon QuickSight predictive analytics using Amazon SageMaker Canvas can be a powerful tool for improving operational efficiency. By identifying bottlenecks, inefficiencies, waste, errors, and other areas for improvement, businesses can reduce costs and improve productivity.

For example, This can be a powerful tool for improving operational efficiency by helping businesses to:

• Identify areas where processes can be improved.
• Allocate resources more efficiently.
• Reduce waste and errors.
• Improve preventive maintenance.

Improve machine maintenance:

You can use Amazon QuickSight and Amazon SageMaker Canvas to build a predictive dashboard that improves machine maintenance. This information can then be used to prevent machine failures and reduce downtime.

For example, you could build a dashboard that shows the following metrics for each machine:

• Machine operating temperature
• Vibration levels
• Oil pressure
• Running time

You could then use Amazon SageMaker Canvas to build an ML model that predicts when a machine is likely to fail based on these metrics. Once the model is trained, you can publish it back to Amazon QuickSight and use it to schedule preventive maintenance tasks.

Available Regions:

Predictive analytics in QuickSight is now available in US East (N. Virginia), US West (Oregon), US East (Ohio), Europe (Ireland), Europe (Frankfurt), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Seoul), Asia Pacific (Mumbai) regions.

Conclusion

Amazon QuickSight's new support for predictive analytics using Amazon SageMaker Canvas makes it easy for anyone to build predictive dashboards. This new capability can help you make better business decisions by enabling you to predict future outcomes.

If you are looking for a way to improve your business intelligence and decision-making, we at Agilisium encourage you to consider using Amazon QuickSight and Amazon SageMaker Canvas for predictive analytics. To learn how to go about integrating both for the benefit of your organizational growth through data insights speak with our experts today!

‍