During a recent webinar, we walked through the simple process of configuring Cube atop your current data sources, establishing integration with Explo, and swiftly creating and embedding dashboards in less than 30 minutes. If you missed that session, we've got you covered.

Why Cube + Explo for Customer-facing Analytics?

Let's start with the definition and use case of customer-facing analytics (CFA). CFA refers to the service of providing data insights, visualizations, and reports directly to customer end-users. SaaS companies, in particular, commonly provide their customers with pertinent data, reports, and dashboards. This empowers their end-users to make well-informed decisions and acquire insights into their engagements with a product, service, or platform.

Why is Customer-facing Analytics a Game Changer? 

By making analytics accessible to end-users of all technical proficiencies, businesses can enhance transparency, improve customer engagement, and empower clients to understand and optimize their experiences. 

• Informed Decision-Making: It provides end-users with valuable insights that allows them to make data-driven decisions, which  improves their experience with the SaaS solution. 
• Competitive Advantage: Organizations that provide robust customer-facing analytics gain a competitive edge. It demonstrates a commitment to customer success and a willingness to share valuable insights, setting them apart in a crowded market.
• Customer Engagement: By sharing analytics, companies foster transparency and engagement with their customers. This not only builds trust but also encourages a collaborative relationship where customers feel more involved and connected to the product or service.

Introduction to Cube

Cube is a universal semantic layer that tackles the menace of data chaos by seamlessly connecting diverse data sources to multiple downstream applications. Cube’s platform offers a suite of features, including robust data modeling, access control mechanisms, a caching layer known as Cube Store, and APIs tailored for different applications. By addressing challenges like data inconsistency, security concerns, performance optimization, and flexibility, Cube emerges as a comprehensive solution for businesses navigating the complex landscape of data analytics.

Why is Cube Different?

• Cube is built for maximum interoperability with all of your data sources and downstream applications. Bring all of your relational databases, cloud data warehouses, query engines, data lakes and time series databases together into one consistent logical data model.
• Define metrics once in Cube and make them available to everyone in your organization. Keep everyone on the same page with a single source of truth and metric definitions maintained in version control.
• Improve query performance and reduce costs by leveraging Cube Store - our world class aggregate-aware caching and pre-aggregation engine.

Introduction to Explo

Explo is an embedded analytics solution that connects directly with databases and solutions such as Cube. Explo stands out with its user-friendly, low-code interface that empowers users to effortlessly create dashboards and reports.

Explo's focus on external users is evident in its dashboard and report builder products. The platform ensures data security and allows for white-labeling, providing businesses with a customizable and secure environment. Designed with non-technical users in mind, Explo offers scalability for handling large numbers of clients, making it an attractive solution for businesses of all sizes.

Why is Explo Different?

• Accelerate time to value: Explo is built to minimize development time and accelerate embedded analytics deployment with templates, low-code tools, and generative AI for report generation.
• Designed for your end-user: Unlike legacy BI solutions, Explo is built for embedded customer-facing use cases. Explo gives your end-users the customization, security, and analytics experience they want via dashboards and self-serve reports.
• Unparalleled Support: Explo provides a dedicated and responsive support team to ensure a quick implementation and long-term partnership. Think of Explo as an extension of your product team.

Getting Started with Cube + Explo for Customer-facing Analytics

In the realm of data integration and readiness, setting up Cube has never been easier. With a straightforward cloud deployment, you open the gateway to a world of possibilities for connecting Cube to diverse data sources. Whether it's databases, files in S3, CSV files, or more, Cube effortlessly bridges the gap.

The first step is defining "cubes" on the Cube platform, akin to datasets, complete with measures and dimensions. A cube can be intricately crafted, pointing to a single table or leveraging advanced queries with joins, offering perks such as pre-aggregations and caching for enhanced performance. These cubes serve as the foundation for the insights to come.

Above the cubes lie the invaluable views, accessible to tools like Explo. The connection between Explo and Cube is established through the SQL API, facilitating a seamless integration that empowers users to explore Cube views directly within the Explo interface in a matter of seconds.

Once integrated, Explo opens the door to a dynamic dashboard-building experience. Users can effortlessly query the data using Postgresql and the intuitive point-and-click builder. To further tailor the user experience, set up customer groups within Explo, ensuring that end users only access their designated data. Customize the look and feel of dashboards to align with your preferences, and, for a touch of integration magic, embed Explo into your application with just a few lines of code.

In essence, the synergy between Cube and Explo creates a powerful ecosystem for data exploration, enabling users to seamlessly connect, analyze, and visualize their data with unprecedented ease and efficiency.

Conclusion

By leveraging the Cube and Explo integration, users are able to enable embedded analytics within minutes for their users. Cube offers a powerful semantic layer, to unify data across data sources, and provide performant data access and querying, while Explo expedites the time to build and launch embedded analytics for end users. 

Ready for customer-facing analytics?:

• Get Started with Cube
• Get Started with Explo
• Watch the On-Demand Webinar