Agile, Scalable, and AI-Ready: The Data Product Platform You’ve Been Waiting For

The last decade has brought an explosion of innovation in data, with cloud data warehouses, the ‘modern data stack,’ and AI leading the way. Data teams have fallen in love with technical problems, and the challenge of integrating point solutions has created a lot of work — but does any of it meet our users' fundamental needs of agility, trust, and speed?

While we were distracted, a new approach to delivering analytics emerged — one that centers on user experience and delivers more, faster, using techniques borrowed from software engineering. We call this data and analytics product thinking.

The data and analytics product approach requires data teams to adopt new methodologies and ways of working that more closely mirror app development teams than the data warehouse teams of the past.

Are existing analytics platforms ready for this transition? Looking over the landscape of disconnected point solutions and antiquated desktop BI, the answer is a resounding no. That’s where GoodData comes in.

From Disconnected Tools to an Integrated Data Platform

GoodData’s new approach offers an integrated, end-to-end data product platform that combines performance, scale, and cutting-edge features to build and deliver insights and AI experiences where users actually make decisions — rather than trapped in an unloved BI interface no one uses.

GoodData has three components

• GoodData BI: A self-service, multi-tenant BI tool with embedded analytics and analytics-as-code capabilities.
• GoodData AI: A generative AI toolkit that enables conversational analytics, search-driven insights, and ML automation.
• GoodData Analytics Lake: A hybrid storage and query engine that optimizes performance across Iceberg (cold storage) and DuckDB (hot storage).

Underpinning it all is our auto-scaling, multi-tenant architecture that delivers speed and operational efficiency in any data center — whether as a managed SaaS solution, deployed in your cloud instance, or even on-premise.

What Sets GoodData Apart

1. AI, BI, and data platform in a single integrated system: No need to waste years cobbling together point solutions.
2. No Code / Low Code / All Code Options: 10x data engineers and self-service users collaborate on the same tools thanks to our mix of easy-to-use AI with powerful, API-first developer features.
3. Trust meets flexibility: Centrally governed models + flexible self-service. Advanced access controls and compliance-ready features, ensuring secure and traceable analytics workflows for enterprise-scale deployments.
4. Built for speed: Auto-scaling infrastructure, in-memory processing. High-performance data querying across cold (Apache Iceberg) and hot (DuckDB) storage, offering a balance of cost-effectiveness and speed.
5. Multitenancy: Scalable workflows and strong access controls make it easier for companies to securely deliver analytics across multiple teams and clients.
6. Customizable Front-End & SDKs: White-label dashboards, reports, and visualizations, with React SDK and API-based embedding, enabling seamless integration into any application.
7. Automation: Integration with CI/CD and data pipelines makes deploying and managing complex analytics environments easy for any team.
8. Composable Semantic Layer: Centralized, reusable data models with tenant-specific customizations, allowing businesses to tailor their analytics without reinventing the wheel.

Conclusion: Own Your Data, Build Your Future

GoodData is more than just an analytics platform — it’s a scalable solution for creating AI-powered, revenue-generating data products. Whether you're a developer, business leader, or data engineer, GoodData offers the performance, flexibility, and scalability needed to drive the next wave of innovation in analytics.

Interested in seeing it in action? Schedule a demo today to learn how GoodData can optimize your analytics strategy. Want to explore on your own? Try GoodData for free and see how it fits into your tech stack — no commitment required. Developers can also check out our GitHub repository to build and customize their data solutions.