Data lakehouse was implemented by Crystal Magnate in this case study. Do you know why and how Sawaat was involved?
Who Is Crystal Magnate?
Crystal Magnate is a leading tech executive partner for e-commerce growth, providing combines technology and consulting business with advanced analytics, and AI solutions to help clients scale and optimize their businesses.
The Strategic Move: Advancing to Next-Level
Crystal Magnate already operated a strong ERP system with reliable reporting for their e-commerce clients. The business was running smoothly — but the leadership wanted to move to the next level. They recognized an opportunity to enhance their platform with advanced analytics and AI-driven insights that could deliver deeper forecasting, performance intelligence, and growth visibility for their clients.
To reach that next stage, they needed a unified and scalable data foundation. They required a modern solution capable of securely integrating ERP data with external ecosystem sources such as Walmart, Amazon Seller Central, Amazon Insights, Google Analytics, and other marketplaces. While they hadn’t explored a Lakehouse before, the goal was to build an infrastructure that would support future expansion, smarter automation, and differentiated value.
The Turning Point: Choosing a Modern Solution
Crystal Magnate approached Sawaat with the objective of taking their data capabilities to the next level — enabling secure data consolidation, stronger governance, and the ability to deliver advanced analytics and AI solutions to their clients. They wanted an architecture that would support growth, multi-client expansion, and seamless onboarding without constant system redesign.
Sawaat evaluated the landscape and recommended a modern Lakehouse framework as the foundation. The team outlined multiple technology paths, including a Databricks-based architecture deployed on either Azure, AWS, or Google Cloud — depending on scalability, cost, and integration preferences each capable of supporting governed data storage, enterprise security, and scalable analytic workloads.
After reviewing Crystal Magnate requirements and budget priorities, Sawaat proposed implementing the Lakehouse using Microsoft Fabric. This approach provided the right balance of governance, flexibility, and cost-efficiency. Sawaat architected the system with a enterprise grade lakehouse and isolated sub-lakehouses for each client, ensuring compliance, clean data separation, and easy client onboarding.
The platform was deployed using a small but scalable Fabric capacity — minimizing upfront cost while allowing resources to expand seamlessly as data volume and client demand grow.
Now, Crystal Magnate has a secure, governed, and future-ready data foundation — positioned to deliver advanced analytics, automated insights, and AI-driven capabilities across all current and future clients, without operational overhead or architectural rework.
Why Sawaat?
Crystal Magnate chose Sawaat because of its boutique consultancy focus on enterprise-grade data lakehouse implementation combined with expert knowledge in cloud, analytics, and data governance. Sawaat’s solution offered a unique blend of:
- Minimum capacity deployment with enterprise-grade architecture,
- Scalable framework accommodating growing customer numbers,
- Integration of multiple key data sources including ERP and marketplace data,
- End-to-end process design ensuring compliance, governance, and secure code management,
- Enablement for Crystal Magnate to build AI and advanced analytics on a solid, extensible platform.
The Transformation: Building a Unified Data Lakehouse
Sawaat then executed the solution by building a full lakehouse on Microsoft Fabric, integrating data from Amazon Seller Central, Walmart, QuickBooks, and product search workflows. The architecture followed a bronze-silver-gold layered model for governance, data quality, and analytics readiness.
To ensure long-term reliability and maintainability, Sawaat also established:
- Enterprise-grade code and version control
- Compliance and data governance standards
- A standardized process for onboarding new data sources
- Modular workflows for future expansion
This setup empowers Crystal Magnate to ingest, manage, transform, and analyze data consistently — while maintaining flexibility to scale as their client base and data needs grow.
The Results: Analytics & AI Solutions with Built-In Security
After implementation, Crystal Magnate achieved analytics, streamlined governance, and enhanced security. Their clients now benefit from actionable insights, automated reporting, and AI-driven decision-making. The platform is highly scalable, secure, and easy to maintain, empowering Crystal Magnate to deliver next-gen analytics to their e-commerce clients.
Ready to transform your new or existing data solution with enterprise-grade scalability and AI-powered insights? Discover how Sawaat’s tailored Data Lakehouse Solutions can unlock your business’s full potential .
