Deliver enhanced analytics: Sisense and AWS Redshift

You’re looking to deliver embedded analytics for your product. Your users are demanding it. However, there are some crucial challenges that every product team faces. These challenges will almost certainly include integrating data from multiple sources, designing a user-friendly analytics experience that melds with your product, scaling to handle increased data and user loads, and optimizing performance. And there’s one more thing: Ensuring the analytics functionality you deliver stays at the cutting edge when it comes to traditional dashboards, ad hoc analysis, and providing the latest in AI and machine learning.

This may sound like a tall order. But the key to overcoming these challenges can be simplified. Here’s what’s needed:

1. A data warehouse to combine your data and deliver strong, scalable query performance without operational headaches.
2. A composable platform that enables your product team to choose from a rich palette of visualizations, and a broad range of analytics capabilities.

Infuse all of the above into your product so that it’s easy and intuitive for your end-users to work with. In this post, you’ll learn how Sisense Fusion and Amazon Redshift Serverless work together so you can provide your end-users with a powerful and integrated data analytics experience that is fast, intuitive, and elastically scales. Learn more about rapidly developing embedded data experiences and adding value to your product offerings with Sisense Fusion Embed.

Database and platform harmony

The real secret is that everything has to work together: your database for analytics must work in harmony with your analytics platform. That way, it’s easier for developers to build and iterate, and users will see the benefits as their data and demands increase.

This is why Sisense is an AWS Data and Analytics Competency partner. Not only does the partnership provide product teams with a comprehensive platform for building analytics, but that platform runs hand-in-hand with Redshift. The result is that product teams can deliver the best experience to customers and end-users, from data to dashboard.

Example: Running Sisense and Redshift together

Let’s say you’re planning to deliver in-product analytics or provide analytics to your end-users across your organization. You’d use Redshift Serverless to automatically provision data warehouse capacity, and to intelligently scale database resources with data and query demands. This enables your product team to focus on providing the best analytics experience for end-users, rather than getting bogged down in provisioning and managing resources.

You’d use Sisense as your analytics platform, for both data prep and transformation to flow data into Redshift. This way, that data is fitted to the needs of your end-users, meaning that it provides specific analytics functionality; from dashboards to reports, to analytics. Using Sisense, your product team would then tap into the robust functionality of Compose SDK. The SDK enables you to infuse your product with analytics components, ranging from traditional analytics, to predictive- and natural language-powered analytics. It’s all completely blended with your app.

Because both Redshift and Sisense work together, your product team doesn’t have to worry about gluing together analytics with data. Instead, Sisense natively works with Redshift to enhance your team’s productivity and accelerate your time to market.

By tapping into the elasticity and ease of deployment of Redshift, and the full-fledged embeddable analytics that Sisense provides, you can get to market fast and efficiently. At the same time, you’re providing a broad range of capabilities in your app to your customers and end-users, including:

• Data visualization: Interactive dashboards, ad hoc analytics, and reporting are all embedded directly in your app. They all flow data from Redshift to your end-users.
• Predictive analytics: The AI-powered forecasting allows your users to clearly see future trends. It helps them to be proactive about decision-making.
• Natural language querying: A conversational experience that fosters engagement by enabling your end-users to ask questions in plain language, and even get narrative answers around explaining data.

Build on a foundation of data and elastic data warehousing

Deploying analytics means ensuring you have an agile and scalable data foundation. After all, you don’t want data to be the roadblock to your success. The following abilities are essential:

1. The ability to rapidly deploy infrastructure resources to support your data analytics initiatives.
2. The ability to handle fluctuating data volumes and user loads without sacrificing performance.
3. The ability to efficiently manage and store growing amounts of data.
4. The ability to optimize resource utilization and control costs.

Amazon Redshift Serverless is designed to enable teams to address the areas above. With its serverless architecture, product and delivery teams can eliminate the need for manual cluster management, reducing both operational overhead and costs.

In addition, teams can use Amazon Redshift Serverless to automatically scale compute and memory resources on-demand, ensuring optimal query performance even during peak workloads.

The usage-based pricing model further enhances cost efficiency. Based on actual queries executed, it allows for flexible and cost-effective data analytics, and for organizations to align their costs with demand.

Learn how to connect Sisense Fusion to Amazon Redshift Serverless.

Flow your Redshift data into intuitive insights for your end-users

Data is only as strong as how you deliver it, and ensuring it gets to the right users—in the ways that make sense to them—is foundational for success. That’s why Sisense works closely with Redshift: to turn data into insight. Sisense connects directly to Redshift databases, tables, and views, with a connection that is specifically optimized to minimize run-time and query execution and maximize performance to deliver the near-instant responsiveness expected by end-users.

Getting the most out of Redshift data requires providing the best way for users to visualize and analyze it within the context of their everyday workflows. For product teams, Sisense Compose SDK enables them to deliver exactly that; by providing a composable, code-driven approach to embedding analytics. Front-end engineering teams can leverage client-side libraries and components to build custom analytics and data-driven experiences into their products that source data from Redshift or other data sources. Whether it’s embedding interactive dashboards, embedding the ability to generate ad-hoc visualizations, or providing self-service analytics features, Compose SDK gives teams the tools they need to deliver a rich analytics experience within their own applications.

Read how Sisense is helping businesses achieve their goals with AI-driven analytics.

Bringing it all together: Connect, build, infuse

Strong integration between your data and analytics has another powerful benefit: facilitating experimentation and rapid iteration. Elastic, on-demand delivery allows product and development teams to start small and easily scale as data needs grow. It’s why Sisense is designed to leverage Redshift infrastructure even if your organization is without a dedicated data engineering team.

Sisense takes advantage of the responsiveness of Amazon Redshift Serverless to power interactive queries and dashboards that are always up to date, with no replication lag. This translates to simplified data pipelines and models, optimized query performance for near-instantaneous responses, and always-up-to-date data.

Integrating closely with Redshift, Sisense Fusion’s API-driven approach allows for flexible deployment options and a highly extensible framework. What this means: Product teams can deliver customizable analytics experiences tailored exactly to how their end-users engage.

Try Sisense on AWS via AWS Marketplace.

Why eCommerce provider Radial runs AWS and Sisense

Together, Sisense and Redshift are helping AWS customers everywhere deliver analytics both across their organization, and to their customers and end-users. For example, Radial is a leading B2B eCommerce company that provides omnichannel support, fulfillment services, payments and fraud protection, and customer care services. They realized they needed to modernize their analytics program to get the most out of their data and deliver a world-class experience to their business teams and customers.

A key goal was to move to a unified approach, from data to analytics. Using Sisense, they connected all their datasets using modern ETL/ELT processes, used a data foundation to provide analyses on fast-moving datasets, and built a user experience that provided analytics in ways that made sense to their specific users.

Before running Sisense and Redshift, Radial’s end-users needed to log into multiple applications to access order management or fulfillment information, fraud insights, or anything else they wanted to know. Now they have a centralized portal via the “Radial Reporting and Analytics” offering, with insights infused into their daily experience, from trusted centralized data.

By combining Sisense and Redshift, Radial moved away from silos and toward robust data integration. The result: A significant boost in operational performance, increased customer satisfaction, and maximized revenue across departments, including order management, fulfillment, and customer care.

Start your journey by unifying data and analytics

Sisense Fusion and Amazon Redshift Serverless enable organizations to take a unified, integrated, and connected approach to deliver analytics. Sisense provides a comprehensive suite for data preparation and analysis, visualizations, as well as capabilities to build analytics into applications; while Redshift Serverless offers a scalable and cost-effective data warehouse platform. Together, they empower product and development teams to deliver relevant data-driven decisions at the point of need, ultimately improving delivery efficiency and the best end-user experience.

To learn more about analytics solutions that will keep you competitive, schedule a demo.