DataRiseLab provides a full‑stack data management platform on Microsoft Azure that consolidates disparate data sources into cloud‑native lakes and warehouses, automates ETL/ELT pipelines, and delivers self‑service Power BI dashboards. The platform also includes custom .NET/Angular applications and Azure Machine Learning models for predictive analytics, all with built‑in security, governance, and migration services for mid‑size to large enterprises.
Funding
Funding not disclosed
Founders
Product
Problem
Many organizations operate with siloed data sources, manual reporting pipelines, and limited visibility into advanced analytics, which hampers timely decision‑making and increases operational costs. Migrating legacy workloads to a secure, scalable cloud environment while maintaining data quality and governance adds further complexity.
Solution
DataRiseLab delivers a full‑stack data management platform that consolidates disparate data into cloud‑native warehouses, automates ETL/ELT workflows, and layers business intelligence dashboards for self‑service reporting. The service suite includes custom business applications built on .NET/Angular that integrate directly with the data layer, enabling end‑to‑end process automation. Predictive and recommendation models are trained on the consolidated data using Azure Machine Learning, providing actionable forecasts and personalization. All components are deployed on Microsoft Azure with built‑in security, role‑based access, and compliance controls, and are supported through ongoing monitoring and maintenance. By handling architecture, migration, and governance, DataRiseLab lets clients focus on core business outcomes rather than data engineering.
Target Audience
Primary customers are mid‑size to large enterprises in finance, hospitality (HoReCa), real estate, and other data‑intensive sectors that require integrated data warehouses, BI reporting, and AI‑enhanced decision support.
Features
- Azure‑based data lake and data warehouse architecture with automated ingestion via Azure Data Factory and Synapse pipelines
- Master Data Management framework that enforces data quality, lineage, and GDPR‑compliant governance
- Power BI reporting suite with pre‑built dashboards, drill‑through, and comment/approval workflows for self‑service analytics
- Custom web applications (.NET Core, Angular) that embed BI visualizations and expose transactional data through secure APIs
- Machine‑learning pipelines (Azure ML, Python/Scala) for predictive analytics, recommendation engines, and generative text models
- CI/CD deployment pipelines using Azure DevOps for repeatable, version‑controlled releases of data and application assets
- End‑to‑end security stack: encryption at rest and in transit, Azure AD authentication, role‑based access control, and audit logging
- Cloud migration and optimization services that assess on‑premise environments, design lift‑and‑shift or refactor strategies, and manage cost‑effective scaling