- Data lake for a German Energy Conglomerate
- US-based Digital Workflow Solutions Provider
Sunshine
Data modernization is a critical aspect of digital transformation initiatives that organizations are embarking upon. Today, more than ever, organizations are producing and consuming diverse datasets and data volumes at a rate that existing legacy data warehouses and on-premises systems cannot handle at scale. Organizations are upgrading to modern data warehouse platforms like Azure Synapse dedicated pool and Microsoft Fabric Lakehouse/Warehouse. Microsoft Fabric reshapes how business teams work with data by bringing everyone together on an end-to-end analytics platform built for the era of AI. It combines data integration, enterprise data storage on OneLake, AI models, and analytics governed by a central governance tool, all in a single managed Software-as-a-Service (SaaS) platform.
Sunshine reduces the manual effort required to move from on-premises to the cloud by making your data migration journey timely, predictable, and cost-effective.
Our Framework
Sunshine provides end-to-end automation in migration from on-premises to Azure, right from pre-migration strategy to post-migration optimization.
- Examiner: helps in a complete assessment of on-premises data warehouse w.r.t. complexity, compatibility, etc.
- Code Convert: converts DDL/DML/business logic to Azure synapse-specific code
- Data Upload: one-time historical upload of data from on-prem to Azure synapse
- Data Auditor: Data reconciliation post-migration of data.
- Supports migration for 5+ on-premises appliances
- Supports migration to Azure Synapse, Azure SQL, and Microsoft Fabric
- Finops is a cloud management discipline enabling organizations to get maximum business value from the cloud.
- Sunshine Finops provides a unified portal with detailed utilization monitoring and cost analysis for Azure Data services including Synapse SQL Dedicated pool, Data Factory, Databricks, SQL, analysis services, etc. thus, providing insights and recommendations for cost optimization and performance optimization.
Automated framework to quickly ingest data from various sources and provide basic data quality and data profiling of the ingested data.
- Metadata-driven ingestion framework with extended features.
- Inbuilt DQ rule engine
- Data profiling reports