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Legacy systems create hidden costs and bottlenecks:
Why Modernize Your Data Architecture?
Slow, expensive analytics
Queries take hours, not seconds.
Poor scalability
Data growth breaks monolithic solutions.
Silos and duplication
Teams can’t trust or find the data they need.
AI/ML roadblocks
Models fail due to weak pipelines and missing metadata.
We build modern, agile, and cost-efficient architectures tailored to your business, whether you’re migrating to the cloud, implementing a lakehouse, or enabling real-time AI.
Our Core Principles for Modern Data Architecture
Principle
Description
Technology Example
Hybrid
Supports cloud, on-premise, and edge deployments
Databricks Lakehouse on AWS + Azure
Data as a Product
Domain-oriented ownership following Data Mesh patterns
Uber-style data domain ownership
Automation
AI-assisted metadata, quality, and security management
Informatica CLAIRE, IBM Watson
Real-Time
Combines streaming and batch data flows
Kafka + Spark Structured Streaming
Openness
API-first and open-source friendly architectures
Snowflake + Apache Iceberg
Audit & Roadmap:
- Full audit of existing systems (DWH, lakes, pipelines).
- Identify cost and performance inefficiencies.
- ROI-based modernization roadmap.
Architecture Design
We deliver cloud, hybrid, and multi-cloud architectures, including:
- Cloud Data Warehouses (Snowflake, BigQuery, Redshift).
- Lakehouse Platforms (Delta Lake, Apache Iceberg).
- Data Fabric (IBM Cloud Pak for Data, Talend Data Fabric, Informatica IDMC, Denodo)
- Real-time & streaming (Kafka, Flink).
- Flexible multi-cloud setups (AWS + Azure + On-Prem).
Our Approach
Migration & Optimization
- Zero-downtime migrations from legacy systems.
- Automated pipeline redesign (SQL → Spark/dbt).
- Cost governance: right-sizing compute and storage tiers.
Future-Proofing
- Scalability for AI/ML workloads.
- Metadata and lineage layers for discoverability.
- Vendor-agnostic solutions (avoid lock-in).
Key Technologies We Use
Category
Open-Source
Enterprise
Storage
Snowflake, Databricks, Oracle, AWS
Apache Iceberg, Delta Lake
Processing
Azure Synapse, AWS EMR
Spark, Flink
Orchestration
Informatica, Talend
Airflow, Dagster
Governance
Collibra, Alation
DataHub, OpenMetadata
Data resilience in an uncertain world
Recent global and regional disruptions have reminded many organizations that data infrastructure resilience is a critical part of business continuity.
Companies are increasingly reviewing where their data is stored, how dependent they are on a single vendor or cloud region, and whether their architecture allows them to quickly recover or relocate workloads if needed.
Modern data platform architectures - including multi-cloud, hybrid, and open-source-based solutions allow organizations to reduce vendor lock-in while improving operational resilience and long-term flexibility.
For more than a decade, SoDa has been helping organizations design and build modern data platforms, including large-scale open-source data warehouses and lakehouse architectures as well as complex data migrations between data warehouses, cloud platforms, and hybrid environments and transitions from proprietary systems to flexible open ecosystems, ensuring continuity while minimizing operational risk.
Ready to modernize your data architecture for real-time insights and AI?
Request an Architecture Review