Build Your Single Source of Truth. We design, build, and modernize data warehouses that bring order to your fragmented data. By consolidating information from disconnected systems into a unified, high-speed resource, we provide the reliable foundation you need for accurate reporting and clear business intelligence.
You have critical data in your ERP, CRM, marketing tools, and spreadsheets. Because these systems don’t talk to each other, you spend hours manually stitching reports together instead of analyzing the results.
Your current system creates bottlenecks. When leadership asks a question, it takes IT days to run the query or generate the report. By the time the data arrives, it’s already stale.
Sales says revenue is X. Finance says it’s Y. Without a centralized data warehouse, different departments define metrics differently, leading to endless meetings about whose numbers are right.
Your existing on-premise warehouse is expensive to maintain and crashes under heavy loads. You want to move to the cloud for scale and cost-savings but aren’t sure how to migrate without disrupting operations.
You want to implement predictive analytics or AI, but your data is too unstructured or fragmented to train models effectively. You need a modern architecture to support advanced use cases.
We don’t just build databases; we build the system behind your decision-making. We make sure your data warehouse is scalable, cost-effective, and designed for the people who actually use it.
Our primary goal is centralization. We architect solutions that pull data from every corner of your business into one unified, governed repository. This means that whether you are in Marketing, Finance, or Ops, everyone is looking at the same trusted metrics.
The days of massive, expensive on-premise servers are over. We specialize in modern cloud data warehouses (like Azure Synapse and Snowflake) that allow you to separate storage from compute. This means you pay only for what you use and can scale up performance instantly during peak times.
We design data models based on your business questions, not just your source system structures. We optimize your warehouse for read-performance, meaning your Power BI dashboards load instantly and your analysts can run complex queries without slowing down the system.
From architectural blueprints to the final data pipeline, we handle it all.
A data warehouse is a complex piece of engineering. Unlike generalist IT firms, we are specialized data architects and engineers. We handle the entire lifecycle: designing the schema, building the pipelines that move the data, and optimizing the query performance. You don’t need separate vendors for migration and management—we build the foundation that supports your business intelligence.
We design the blueprint for your warehouse (Star Schema, Data Vault, etc.) so it is optimized for fast reporting and easy scalability.
We build the automated “pipes” (using Azure Data Factory or similar tools) that extract data from your source systems, clean it, and load it into the warehouse.
We securely move your data from legacy on-premise servers (like SQL Server or Oracle) to modern cloud platforms with minimal downtime.
We optimize your queries, indexing, and partitioning so that reports load in seconds, not minutes, even as your data grows to petabytes.
We connect your new data warehouse directly to visualization tools like Power BI, providing seamless access for end-users.
With us, your data warehouse becomes a high-performance asset that grows with your company.
Building a data warehouse requires deep technical knowledge of specific platforms. We bring certified expertise to make your architecture bulletproof.
We turn fragmented data streams into a centralized view for high-level decision-making. This dashboard example demonstrates how a Data Warehouse consolidates information from Sales (CRM), Finance (ERP), and Logistics (WMS) into one strategic view.
Let’s talk about your current data infrastructure and where you want to take it. Let’s jump on our initial strategy call, there’s no obligation. You’ll walk away with a clear understanding of how to modernize your data architecture for speed, scale, and cost savings.
We’d like to ask you a few questions to better understand your IT needs.
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Data warehouse consulting services help organizations design, build, modernize, and optimize centralized data platforms for reporting, analytics, and decision-making. Consultants provide expertise across architecture, integration, migration, performance, and governance.
Typical services include:
Data warehouse architecture design
Cloud data warehouse implementation
ETL / ELT pipeline development
Data integration across systems
Legacy warehouse modernization
Performance and cost optimization
Governance and security framework setup
The goal is to create a scalable “single source of truth” that supports business intelligence and advanced analytics.
A data warehouse consultant designs and implements enterprise data platforms that consolidate data from multiple systems into one trusted analytics environment.
Key responsibilities include:
Designing data models (Star, Snowflake, Data Vault)
Building ETL / ELT pipelines
Integrating ERP, CRM, and operational systems
Migrating legacy warehouses to the cloud
Optimizing query performance
Implementing governance and access controls
Enabling BI and dashboard reporting
Consultants also establish best practices so internal teams can scale and manage the platform long-term.
Data warehouse implementation services cover the full lifecycle of building a production-ready analytics platform.
A standard implementation includes:
Requirements discovery and architecture design
Cloud infrastructure setup
Data ingestion and pipeline development
Data modeling and schema design
Integration with business systems
Performance tuning and testing
BI tool connectivity
Documentation and knowledge transfer
This ensures your warehouse is scalable, secure, and optimized for analytics workloads.
Organizations typically hire data warehouse consultants when internal systems can no longer support analytics and reporting needs.
Common triggers include:
Data silos across departments
Slow or unreliable reporting
Conflicting metrics across teams
Legacy infrastructure limitations
Cloud migration initiatives
AI and advanced analytics adoption
Consultants accelerate transformation while reducing implementation risk.
Implementation timelines vary based on complexity, scale, and data maturity.
Typical ranges include:
Discovery & architecture design: 2–4 weeks
MVP / pilot warehouse: 4–8 weeks
Departmental warehouse: 2–4 months
Enterprise warehouse transformation: 4–9+ months
Phased delivery models allow organizations to generate value early while expanding capabilities over time.
Data warehouse consulting costs depend on technical scope and organizational complexity.
Pricing is influenced by:
Number of data sources
Data volume and velocity
Migration complexity
Platform selection
Governance requirements
Performance SLAs
Integration depth
Engagements may be fixed-price projects, time-and-materials, or ongoing managed services.
Several architectural and operational factors drive consulting investment levels.
Key cost drivers include:
Legacy system complexity
Data quality and transformation needs
Real-time vs batch processing
Security and compliance requirements
BI and analytics integration scope
Cloud infrastructure design
A discovery assessment is typically conducted to estimate accurate cost and timelines.
Yes — migrating legacy data warehouses to cloud platforms is a core consulting service.
Migration services typically include:
Legacy system assessment
Data mapping and transformation
Pipeline re-engineering
Infrastructure provisioning
Performance benchmarking
Parallel testing and validation
Cloud migration improves scalability, reduces maintenance costs, and enables modern analytics capabilities.
Yes — consultants support migrations from traditional enterprise warehouse platforms to modern cloud architectures.
Common modernization scenarios include:
SQL Server to Azure Synapse
Oracle to Snowflake
Teradata to cloud data warehouses
On-prem warehouses to hybrid or SaaS platforms
Migration approaches are designed to minimize downtime and maintain business continuity.
Yes — consultants design and implement greenfield cloud data warehouses tailored to business needs.
Cloud warehouse implementation includes:
Platform selection and architecture design
Storage and compute configuration
Data ingestion framework setup
Security and governance implementation
Analytics and BI enablement
This approach creates a scalable analytics foundation without legacy constraints.
Performance and cost optimization are critical consulting services, especially in cloud environments.
Optimization initiatives include:
Query performance tuning
Indexing and partitioning strategies
Compute workload balancing
Storage optimization
Cost monitoring frameworks
Usage and concurrency tuning
These improvements accelerate reporting while reducing infrastructure spend.
Yes — governance and security are foundational to enterprise data warehousing.
Governance services include:
Access control and role design
Data classification frameworks
Audit logging and monitoring
Data lineage tracking
Compliance alignment (GDPR, HIPAA, etc.)
Catalog and metadata management
This ensures secure, compliant, and trusted analytics environments.
Data warehouse consultants typically support all major cloud and enterprise platforms.
Common technologies include:
Snowflake
Azure Synapse Analytics
Microsoft Fabric
Amazon Redshift
Google BigQuery
Azure SQL Database
Platform selection depends on performance, scalability, ecosystem, and cost considerations.
A data warehouse centralizes and standardizes enterprise data to enable accurate reporting and advanced analytics.
Key BI enablement benefits include:
Unified reporting across departments
Self-service dashboards
Faster executive decision-making
Historical trend analysis
AI and predictive analytics readiness
It serves as the analytics foundation powering enterprise data-driven strategy.
