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Key speakers from Cube and Push.ai walked the audience through the benefits and capabilities of integrating Cube, a universal semantic layer, with Push.ai, a technology focused on business observability. Here are five key takeaways from the webinar delivered by Cube and Push.ai.
1. Data Centralization with Cube
As Brian Bickell accurately summarized, the reason for shifting towards a universal semantic layer like Cube is to centralize all data models into one location. Cube lets you model your data once and delivers the same model to all downstream applications. This function promotes data consistency, data security, performance, better developer experience, stack flexibility, and time-to-value. Stored next to data warehouses and utilized to route all processes through the semantic layer, Cube has enhanced the data handling and management landscape.
2. Business Observability with Push.ai
Britton Stamper, the CTO & Co-Founder of Push.ai, introduced their concept of a "business graph." It involves tying measurements from a semantic layer to different departments and owners, constantly keeping each entity aware of business changes. The team at Push.ai has leveraged semantic layers to model businesses, build intelligent products, predict future goals, and encourage companies to grasp their current status. Push.ai employs causal models and regression to facilitate metric analysis, which helps businesses reach their set goals more accurately.
3. Integrated Capabilities of Cube and Push.ai
Zach Mandell demonstrated how Push.ai’s integration with Cube significantly simplifies reporting and allows them to deliver data to workplaces in a precise and easy-to-understand way. Cube’s cloud-hosted platform centralizes data models, providing a universal semantic layer that can be deployed across any cloud provider and region. On the other hand, Push.ai excels at providing personalized analytics for teams and simplifying metric management, pointing out interesting metrics within multiple dimensions. As Zach emphasized, the semantic layer enables Push.ai to easily import metrics from Cube, quickly achieving a comprehensive view of the business.
4. Advantages of the Cube and Push.ai Integration over Similar Tools
Compared to Looker's semantic layer, Cube offers superior security, job tokens, caching with Cube store, and can connect to various databases and downstream tools. Additionally, integrating Cube and Push.ai reduces the database workload, as the system is designed for caching. Moreover, Cube's cloud SaaS offering is distinctively complemented by an open-source project for on-premise deployment, while Push.ai is strictly cloud-based.
5. Proactive Action based on Insights
Integrating Cube and Push.ai fosters the ability to take proactive action based on data insights. For example, users can create notes or annotations, assign action items, and manage workflows around their data, ultimately facilitating a methodical orchestration based on leading indicators of success. Such tools allow businesses to establish a top-down view of the ecosystem and steer their trajectory based on pertinent real-time data.