Legacy warehouses limit scalability, performance, and innovation. They drive up costs, expose security vulnerabilities, and make it difficult to integrate with modern data sources or support ML/AI initiatives. Modernizing these environments is often the first step toward achieving agility, flexibility, and intelligence at scale.
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We help organizations modernize and future-proof their data environments through a well-established migration process. Our proven methodology streamlines assessment, ETL translation, and migration execution while reducing time-to-value and risk through automation and expert validation.
We analyze your current data environment using automated profilers. We capture data volumes, workload classifications (ETL, BI, ingestion), usage patterns, and growth trends. We also identify orchestration details, user behaviors, and potential migration costs to enable precise planning and platform optimization.
During this phase, we evaluate workflow complexity, dependencies, and migration challenges. We provide accurate estimates of effort, cost, and resource requirements so every decision is informed and every risk is anticipated.
During the code conversion phase of data migration, we convert legacy code into modern data warehouse or lakehouse–compatible code, such as PySpark or SQL. We prefer the creation of quick proofs of concept (PoC), MVPs, or pilot solutions, helping organizations jumpstart their migration projects and realize ROI more quickly.
Once the groundwork is ready, we provision new environments, migrate data, and validate every dataset. We use ETL or ELT tools to extract data from legacy systems, transform it as required, and load it into the new warehouse or lakehouse while also ensuring accurate transfers through full loads and incremental syncs. We verify completeness, accuracy, and governance compliance to confirm the success of the migration process.
Once data is migrated, we ensure the new environment meets or exceeds performance expectations. We implement monitoring and alerting for job failures, storage, and compute utilization. We benchmark query response times and monitor ETL job duration to tune compute resources and partitions. We also optimize storage formats for maximum query efficiency.
An official Databricks consulting partner, Arbisoft helps organizations move from legacy data warehouses to the Databricks Lakehouse Platform. With Databricks Lakebridge, we evaluate workloads, usage, and complexity while pinpointing which SQL code, stored procedures, and ETL workflows need manual or automated migration. We then accelerate the migration of logic/code with the Databricks converter and validate results using the reconciler tool.
Organizations face multiple hurdles when migrating data from legacy warehouses to modern platforms. Here’s how Arbisoft helps you tackle them efficiently.
Outdated databases, rigid ETL workflows, and bespoke applications make migrations time-consuming and error-prone. We perform automated discovery and assessment of your data, workloads, and scripts. Our profiling tools capture volumes, usage patterns, and code complexity, helping us plan precise migration strategies.
Incomplete or incompatible transfers can corrupt data or break applications, threatening business continuity. We use automated ETL/ELT workflows to extract, transform, and load data accurately into the new environment. Initial partial migrations are followed by incremental updates to maintain consistency, while validation routines confirm accuracy and reliability.
Big migrations often require systems to go offline, impacting users and critical business functions. We apply an agile delivery model that allows legacy and new systems to run in parallel. Data reconciliation and PoC-driven execution help us reduce downtime while ensuring smooth adoption.
Manual processes, messy data, and complex dependencies inflate project timelines and costs. We leverage automated tools for profiling, assessment, and code conversion to reduce manual effort and accelerate delivery. Our approach includes workflow translation and performance tuning to optimize efficiency, control costs, and shorten migration timelines.
Old warehouses often hinder advanced analytics, reporting, and AI adoption. We modernize your data stack for BI and AI. Post-migration, we optimize query performance, storage formats, and ETL orchestration to help unlock faster insights and smarter decision-making.
Maintaining compliance and secure access during migration is critical but challenging. We replicate governance rules, enforce fine-grained access control, apply data masking, and ensure compliance with standards like GDPR, CCPA, and HIPAA to protect your sensitive data at every stage.
There’s a reason why companies around the world choose Arbisoft for their data migration needs. We bring clarity, consistency, and confidence to every migration journey.
From initial assessment and strategy to execution and post-migration optimization, we manage your entire data migration journey. Our structured approach ensures zero downtime, no data loss, and smooth adoption across your organization.
Our team of data engineers and migration specialists brings cross-industry experience and deep technical expertise. You can trust Arbisoft to handle even the most complex migrations with precision and reliability.
Arbisoft’s proven methodologies accelerate migration timelines without compromising data integrity or security. We employ automated profiling, code conversion, and validation tools to reduce project duration while maintaining flawless results.
Migration is just the beginning. We monitor performance, tune workloads, and optimize queries post-migration to ensure your systems remain efficient, scalable, and ready for innovation.
Years building custom solutions and applications
Partnerships
Technologies Employed
Specialists with decades of experience
Arbisoft partnered with edX to revolutionize education by developing Open edX, an online MOOC platform accessible to everyone. With a team of 150 experts, Arbisoft contributed to the refinement of Studio features, extended the platform to integrate with third-party LMS, and provided timely support to edX learners. Today, over 20 million learners and 140 partners trust edX, a reliable and robust open-source platform.
It helps understand data volumes, usage patterns, quality issues, and growth trends essential for capacity planning and optimization.
Understanding ETL, BI, and ingestion workloads helps prioritize migration steps and assess which scripts require refactoring for the target platform.
It identifies upstream and downstream systems, APIs, and tools that depend on the data warehouse to prevent integration breaks after migration.
We ensure this by replicating the same data governance and security rules, enforcing fine-grained access control, applying data masking, and maintaining compliance with standards such as GDPR, CCPA, or HIPAA.
Tools like Databricks Lakebridge automate code conversion, workload migration, and validation, reducing manual effort and accelerating timelines.
Running the legacy and new systems in parallel allows you to reconcile data and validate reports before decommissioning the old system.
It ensures data lineage, ownership, and quality, building trust in migrated data and supporting regulatory compliance.
Following migration, it’s important to regularly optimize queries, pipelines, and orchestration jobs to improve performance and cost efficiency using cloud-native monitoring tools.
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