Explore detailed examples of how Dataception's innovative data and AI solutions have transformed businesses across various industries. Our case studies highlight the challenges faced by our clients, the tailored solutions we developed, and the significant results achieved. These success stories demonstrate our commitment to delivering impactful, data-driven outcomes and showcase our expertise in solving complex business problems with advanced technology.
D&A teams across the organization who worked in silos (including remote data centers), on different technologies spent cost time & money in duplication & lack of capability to deliver complex use-cases.
Architected a self-serve Data Mesh solution (including delivery model) encapsulating and self-service capabilities for all data and analytics teams use-cases and lifecycle.
Solution architecture Operating model Data architecture
The bank needed real-time reporting on 2000 metrics over risk, cost, capacity, efficiency and performance for the 30 Operations departments on 50Tb of data, with more streaming, daily.
A distributed data mesh platform that could execute 1000s of metrics in real-time on streaming and historical data. 120-million daily/updates/30 domains = avg table 1.4-billion rows.
Metrics catalogue including meta-data driven aggregations, data attributes, dimensions, polices. Platform architecture, metric engines and infrastructure.
AI Models deployed seamlessly by the mesh co-located, by Injection molding machines on factory floor
Data from the molding machine exposed as virtual tables across the mesh
The mesh deploys data products from other departments on the cloud as one seamless experience
Existing systems wrapped in services and new applications build using containerized microservices approach
Higher level GraphQL services composing lower level REST services
Uses Azure cloud native services – AppService, AKS
All channels integrated giving single customer view
Data Virtualization enables fast on-boarding and experimentation
Allows real-time access to Virtual reality “Virtual clubs”
APIs that the web site asks the engine to match collaborations with people.
Includes a number of matching algorithms to create scores for each of the matching requests
Component that creates the feature weights for the matching engine for each of the taxonomy’s
APIs that take in data for the Feature mapping, including Item data(matching requests), user profiles and any reference data
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