As organizations shift toward data-driven strategies, Google Cloud Platform (GCP) has emerged as a leading platform for scalable cloud services, offering cutting-edge tools for data storage, processing, and analytics. However, as data grows in complexity and volume, ensuring consistent access to trusted, governed data across all teams becomes increasingly difficult. This is where Cube’s universal semantic layer comes into play. By integrating Cube with GCP’s advanced infrastructure, businesses can deliver a unified, trusted, and scalable analytics experience across the organization.

GCP provides an ecosystem that includes services like BigQuery, Cloud Storage, and Dataflow, which help companies store and analyze large datasets in real time. However, one common challenge that organizations face is making this data accessible, consistent, and easy to interpret for business users across multiple analytics and business intelligence (BI) tools.

Cube solves this by providing a universal semantic layer that centralizes and governs data definitions, KPIs, and metrics, ensuring that all teams—from engineering to business—access data that is consistent, accurate, and optimized for performance. Together, Cube and GCP unlock the full potential of cloud-scale data for every business user.

A Perfect Pair: Combining Cube’s Universal Semantic Layer with Google Cloud Platform

Unified Data Storage and Simplified Data Access

GCP enables businesses to store massive amounts of structured and unstructured data using BigQuery for data warehousing and Cloud Storage for unstructured data. However, with multiple sources of data and disparate teams accessing it via different tools, ensuring that everyone works from a single source of truth can be a significant challenge. Cube’s universal semantic layer simplifies this complexity by creating a centralized semantic layer that standardizes key metrics, business logic, and KPIs. With Cube sitting on top of GCP’s data infrastructure, business users from various departments can access consistent, trusted data definitions, regardless of whether they’re using Looker, Google Data Studio, Google Sheets, Tableau, or any other BI tool.

Streamlined Collaboration Between Data and Business Teams

GCP provides data engineers and data scientists with powerful tools like Dataflow and BigQuery to manage ETL processes, real-time data pipelines, and complex analytical workloads. However, business users often face challenges in accessing this data due to a lack of technical expertise.

Cube bridges the gap between technical teams and business users by providing an easy-to-use, centralized semantic layer that abstracts away the complexity of GCP’s data architecture. With Cube, business users can self-serve their analytics needs without requiring constant input from data engineering teams, empowering them to query and visualize data independently, yet reliably.

Real-Time Insights at Scale

GCP’s BigQuery is renowned for its ability to handle massive datasets and deliver real-time insights using its serverless architecture. However, while the platform excels at real-time data processing, ensuring that this data is accessible and consistently defined across tools remains a challenge. Cube enhances GCP’s real-time data capabilities by pre-aggregating and caching frequently used queries and metrics, ensuring that real-time insights can be accessed rapidly. Cube integrates with GCP to provide real-time data consistency across various analytics tools, enabling decision-makers to act quickly on the most up-to-date and reliable information.

Faster Time-to-Insight with Optimized Costs

As organizations scale on GCP, the complexity of querying large datasets in BigQuery can lead to increased computational costs and slower time-to-insight, especially for frequently accessed data.

Cube addresses this challenge by pre-aggregating and caching key metrics, offloading the computational burden from BigQuery and reducing the frequency of heavy queries. This results in faster query performance and significantly lower infrastructure costs. By leveraging Cube with GCP, organizations can reduce the time spent on data preparation and query optimization while improving the efficiency of their cloud infrastructure.

Governance and Compliance Across the Entire Data Stack

GCP offers strong data governance, security, and compliance features, including Identity and Access Management (IAM), Data Catalog, and Cloud Security Command Center. However, as data is accessed by multiple teams across a variety of tools, ensuring consistent governance and access controls becomes a challenge.

Cube’s universal semantic layer ensures that GCP’s governance policies are applied uniformly across all BI and analytics tools. By enforcing consistent data governance rules, Cube minimizes the risk of data misuse, ensuring compliance with key industry standards such as GDPR, HIPAA, and SOC 2. With Cube and GCP together, organizations can maintain control and compliance without compromising on agility or ease of access.

Conclusion

By combining Cube’s universal semantic layer with the flexibility and power of Google Cloud Platform, organizations can unlock a unified, scalable, and governed data experience. GCP provides the infrastructure for storing, processing, and analyzing massive datasets, while Cube ensures that this data is consistently defined and easily accessible across the entire business.

Together, Cube and GCP empower organizations to:

  • Democratize data access by enabling all teams to self-serve analytics while maintaining consistent metrics and KPIs across tools.
  • Reduce time to insight by optimizing query performance with Cube’s caching and pre-aggregation capabilities, all while lowering cloud infrastructure costs.
  • Ensure governance, security, and compliance across all data interactions, ensuring that data is not only accessible but also secure and compliant.

Whether your team is building real-time analytics dashboards, driving machine learning initiatives, or powering self-service BI tools, the combination of Cube and GCP delivers a powerful, scalable, and reliable foundation for data-driven success. Cube is available on the Google Cloud Platform Marketplace. Install Cube Cloud for Sheets for free from the Google Workspace Marketplace. Contact sales to learn more about how Cube and GCP work together.