Data Warehouse Modernization
Migrate and modernize legacy EDW infrastructure to cloud-native platforms like Snowflake, Databricks, and Azure with ETL/ELT optimization, data lake integration, and built-in performance tuning and governance frameworks.
Legacy data warehouses weren't built for today's speed, scale, or AI demands. Cybic modernizes your ETL/ELT pipelines and EDW infrastructure on Snowflake, Databricks, and Azure — eliminating data silos, accelerating query performance, and delivering a governed, cloud-ready foundation that powers real-time analytics and enterprise AI across every critical business function.
End-to-end data warehouse modernization services — from legacy EDW migration to real-time pipelines, governance, and cloud-native architecture.
Migrate and modernize legacy EDW infrastructure to cloud-native platforms like Snowflake, Databricks, and Azure with ETL/ELT optimization, data lake integration, and built-in performance tuning and governance frameworks.
Design and optimize high-performance ETL/ELT pipelines for real-time data ingestion, transformation, and loading — enabling low-latency, AI-ready data flow across cloud, hybrid, and on-premises environments.
Strategic advisory on cloud platform selection, semantic architecture, and data integration modernization — with structured roadmaps to resolve siloed data and align infrastructure with AI and analytics readiness.
Conduct data landscape audits, gap analysis, and build governance frameworks with GDPR, HIPAA, and CCPA compliance — defining data ownership policies and strategic roadmaps aligned with business objectives.
Connect AI platforms, data pipelines, enterprise applications, and cloud infrastructure into unified operational systems — enabling seamless exchange between CRMs, ERPs, data lakes, and LLM-powered tools.
Design infrastructure-agnostic, cloud, hybrid, or on-prem architectures with RBAC and encrypted data protection — built to scale across AWS, Azure, and Google Cloud while meeting SOC 2, HIPAA, and GDPR compliance standards.
We begin with a comprehensive audit of your existing EDW, ETL pipelines, data sources, and governance posture — identifying bottlenecks, redundancies, siloed datasets, and gaps in compliance with standards such as GDPR, HIPAA, and CCPA.
See how Cybic has helped enterprises eliminate data silos and unlock real-time, AI-ready analytics.
Cybic delivers data warehouse modernization grounded in engineering precision, governed architecture, and a commitment to operational outcomes — not just slide decks.
Security controls, RBAC, audit trails, and GDPR/HIPAA compliance are embedded at the architectural level — not bolted on afterward.
Experienced engineers architect, build, and integrate directly — minimizing gaps between design and working, production-ready systems.
Solutions operate across cloud, hybrid, or on-premises environments on AWS, Azure, and Google Cloud — without locking you into a rigid ecosystem.
We unify data pipelines, automation logic, and AI models into a single operational system — enabling seamless transition from modernized warehouse to enterprise AI.
A team of engineers and data architects committed to delivering results.
Cybic is an AI engineering company purpose-built to design and deploy enterprise-grade data and AI systems that integrate directly into core business operations. With deep expertise across cloud data warehousing, ETL/ELT pipeline engineering, and governed AI architecture, Cybic has earned the trust of organizations ranging from fast-growing enterprises to global technology leaders including NVIDIA, Google, Microsoft Azure, Databricks, and AWS. Our engineering-led approach means every engagement is structured around implementing working systems — not theoretical frameworks — with transparency, accountability, and security embedded from day one. Trusted across industries including Oil & Gas, Healthcare, Manufacturing, Retail, and the Public Sector, Cybic brings the technical depth and operational discipline required to modernize legacy data infrastructure and position enterprises for AI-ready growth.
ETL data warehouse modernization is the process of migrating legacy enterprise data warehouse infrastructure to modern, cloud-native platforms — redesigning ETL or ELT pipelines to improve data ingestion speed, scalability, and reliability. It typically involves moving to platforms like Snowflake, Databricks, or Azure Synapse, integrating data lakes, and embedding governance controls to support real-time analytics and AI workloads.
Speak with a Cybic data engineer for a no-obligation consultation on your modernization roadmap.
Certified expertise in Snowflake cloud data platform deployments.
Recognized integration expertise on the Databricks data intelligence platform.
Verified cloud engineering capabilities on Amazon Web Services infrastructure.
Tell us about your current data infrastructure and goals. A Cybic engineer will review your requirements and respond with a tailored modernization approach — typically within one business day.