SQream Platform
GPU Powered Data & Analytics Acceleration
Enterprise (Private Deployment) SQL on GPU for Large & Complex Queries
Public Cloud (GCP, AWS) GPU Powered Data Lakehouse
No Code Data Solution for Small & Medium Business
Scale your ML and AI with Production-Sized Models
By noasa
A major banking group discovers the true value of their data when loading, prep and analytics time is slashed by up to 81%, querying goes from hours to minutes, and everyone is on the same page.
“It takes just a few seconds to query one or two years of data with SQream. That frees us to focus more on analytical processes and to be open to more innovation.” (Olson Mutwiri, Senior Data Engineer)
BACKGROUND: GROWING PAINS
The NCBA group is a leading African financial services provider headquartered in Kenya, with subsidiaries across the continent serving over 60 million customers. Its digital banking subsidiary, LOOP DFS, provides online and app-based services in the African market, which leads the world in mobile banking.
As NCBA’s markets and lines of business expanded, the amount of data and intensive processing workloads the digital subsidiary was handling increased, rapidly outgrowing the organization’s existing Oracle data analytics architecture. Critical insights and trends were being missed, which impacted customer service, business development, and employee experience.
NCBA needed to find a cost-effective solution that would address their growing challenges.
SOLUTION: SIMPLIFIED ARCHITECTURE AND DATA-DRIVEN COMPETITIVE ADVANTAGES
The primary alternatives that NCBA explored included an Oracle upgrade and a transition to the Hadoop ecosystem. After a careful assessment, however, the organization determined that the costs and investment required for each of the proposed options could not be justified.
SQream stepped into the breach with blazing-fast performance, a minimal hardware footprint, simplicity, and effortless future scaling possibilities. The enterprise-grade platform with its patented multi-level GPU acceleration for intensive SQL analytics is critical as a cost-effective complement to the Oracle system NCBA uses for transactional banking processes.
Increased productivity
All of NCBA’s data is managed, governed and queried directly in the SQream data warehouse, without the need to move it or make copies. Data engineers are able to tackle anything that the business users throw at them, they are much more productive and don’t have to constantly keep an eye on the data pipeline to prevent crashes.
Better user engagement
Users from all NCBA sites across Africa have direct, stable and fast access to all of the company’s business data and can query SQream whenever needed. Moreover, supervisors can easily and quickly create and manage stakeholder permissions and employee roles on an enterprise level.
Innovation and rapid expansion
Since supercharging its Oracle environment with SQream’s GPU-acceleration and advanced analytics, NCBA is regularly saving almost two extra days on significant data projects. Data is ready when it is needed – not hours or days later.
To see the actual results, download the full NCBA case study
SQream’s streamlining gives NCBA a clear competitive advantage as they expand into new markets or introduce financial services, with timely insights into customer behavior and support for various novel use cases. NCBA data teams are also free to focus more on analytics and innovation, including proactively brainstorming with the business teams.
Cost-effectiveness
SQream is three times less expensive than the data management alternatives NCBA considered, with significantly fewer resource demands and consolidated software simplicity contributing to an excellent ROI. Time is money and SQream’s lightning-speed performance saves users time every day, as well as allowing faster recovery and catch-up in the case of a malfunction or a planned shutdown.
“After we implemented SQream, there was a lot of excitement around the table about the new platform. Personally, it made me feel good that we’re solving problems for our business.”
(Leslie Chemwolo, Head of Data Infrastructure and Engineering)