Cloud Academy delivers data insights 70% faster with Cube Cloud's semantic layer

The Cube x Cloud Academy user story.

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Cloud Academy delivers data insights 70% faster with Cube Cloud's semantic layer
HQSan Francisco, California, United States
StackApache Superset, AWS Redshift
Use CaseConnected Business Intelligence (BI)

What is Cloud Academy?

Cloud Academy is a leading e-learning platform for enterprises looking to teach, refine, and develop a workforce’s technology skills. As a part of the UK-based learning and development company, QA, the platform offers learners a customized experience based on their trajectory, proficiency, and role. With technical subjects such as cloud computing, software development, DevOps, and security, users take assessments and then are given access to courses and hands-on labs tailored to their current skills.

Deliver Better Performance for Embedded Analytics

Back in 2021, QA was struggling with delivering a great analytics experience to their customers. They had integrated a well-known BI tool into their Cloud Academy learning platform and were unsatisfied with the results. The platform was offline too often, adding new elements and modeling the data was slow and inefficient, and the interface didn’t seamlessly integrate into their product as they would have liked. Alessandro Lollo, Data Engineering Manager was committed to delivering a product with CI/CD principles - continuous integration and continuous delivery/deployment - and the BI tool they had integrated was not living up to their standards.

Cube Cloud: Easier to use and more secure for embedded analytics

It took about a month to integrate Cube Cloud into the Cloud Academy platform and then, in less than 3 weeks, they delivered their first Cube-based embedded analytics app to enterprise customers with a data visualization experience that was seamlessly integrated into their product.

Flexible data modeling and pre-aggregation for speed

The team appreciated Cube’s flexible data modeling framework as it made it easier to use their existing data warehouse and much faster to maintain, update, and add elements to their data models. Cube’s fully managed pre-aggregation capabilities allowed them to boost the response times of complex data models and improve their customers' experience.

Developer tools for the Data Engineer

Alessandro was happy with Cube Cloud’s developer toolkit that allowed for easy collaboration and Git-integration that delivered a smoother development process - as well as the zero downtime of the fully-hosted solution. Of course, security is paramount to Cloud Academy, and Cube Cloud’s virtual private cloud (VPC) and VPC peering capabilities in addition to the security context orchestration and role-based access controls allowed Cloud Academy to maintain their high standard of security.

Cube Cloud: 5x increase in speed; 90% less downtime

All-in-all, Cloud Academy was able to speed up releases of new data models into production by 5x while decreasing their platform’s analytics downtime by 90%. But the biggest benefit came over time, as Lollo and his team realized that with the new more tailored, and integrated user experience, more users were taking advantage of these analytics features.

“With Cube, we’ve been able to speed up time to release a new data model to production by 5x and decrease analytics downtime by 90%.” —Alessandro Lollo, Senior Data Engineer

Expanding Cube Cloud to Deliver Data Insights Everywhere

After finding success with their customer-facing analytics, QA’s Cloud Academy team began to turn their attention to internal stakeholders realizing that Cube Cloud’s semantic layer could potentially provide the security orchestration they needed to provide internal stakeholders with insights into how their product was being used: course consumption, learning paths, and key metrics related to the recommendation system. And everyone wanted access to these insights: product, marketing, sales, executives, and other teams that wanted to leverage this data to make key business decisions.

Protecting user data was paramount: Cube Cloud delivered

Cube Cloud’s robust security tools and capabilities were the key to allowing Cloud Academy to share these insights with internal stakeholders while protecting their users' personal data (PII) - of utmost priority for Cloud Academy. With Cube's powerful security context features, Cloud Academy could mask or restrict access to certain fields, depending on which users are accessing data. Additionally, in a multi-tenant reporting use case, Cube’s row-level security is paramount to ensure that external users don't accidentally see unintended data. These complex user and data access control requirements made Cube Cloud the perfect fit.

Developing and delivering faster with Cube Cloud

As before with embedded analytics, Lollo and team appreciated the developer tools and Git-integration that allowed for collaborative development. In particular, the automated testing features that made it easy for the Cloud Academy team to develop and launch new use cases quickly. In fact, the process was so easy that Lollo estimated they could now go from idea to final result 70% faster than before.

“The total time we have to spend between the idea of building a cube or an analysis and delivering to end users is 70% faster than before.”—Alessandro Lollo, Data Engineering Manager

The Future of Cloud Academy’s Semantic Layer

Today, the Cloud Academy data team has Cube Cloud integrated into their customer-facing product and is delivering product and usage insights to internal teams using Apache Superset. But there are more opportunities on the horizon as Lollo considers having Cube Cloud deliver to Hex for additional data exploration.

Cube Cloud’s flexibility leaves Lollo and his team with plenty of room to play and imagine what the future could entail. “I can imagine analysts merging data coming from Cube and maybe attaching some other type of exotic or fancy data coming from - I don’t know!”

“Our analysts have all the freedom they want to store data and do prototyping, but there may be some use cases where they need additional tools. Using the semantic layer here ensures well governed and well defined data, as well as proper access controls.”

Here at Cube, we can’t wait to find out how QA moves forward with this new understanding of the data on their Cloud Academy platform.

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