Data Consulting | Data Warehouse & Data Lake Services

Data Warehouse & Data Lake Consulting

Modernize, migrate, and optimize your data warehouse or data lake—from legacy platforms to production-ready analytics and AI.

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25+

Years of data expertise

100K+

Workloads migrated or managed

45+

Technology specializations

Production-ready data platform solutions

Expert consulting across every major data warehouse and data lake technology.

Canadian retailer accelerates insights with a unified data platform

The customer partnered with Pythian to accomplish a centralized source of truth.

A leading Canadian clothing retailer struggled with siloed data and slow, manual reporting that prevented timely decision-making. By deploying Pythian's enterprise data platform (EDP) quickstart for Google Cloud, the company created a centralized source of truth. The new data platform enables self-serve analytics, allowing business users to access critical insights in near real-time and build a more data-driven culture.

Read the success story ->
Canadian retailer accelerates data insights partnering with Pythian.

Our end-to-end data warehouse and data lake consulting ensures platform modernization success

Pythian’s delivery model navigates complex data environments to ensure your investment translates into measurable business velocity.

We assess your platform's health, identify bottlenecks, and map embedded business logic. The output is a strategic roadmap grounded in your data—not generic playbooks.

We design a target-state architecture tailored to your workloads—covering storage, modeling, security, and integration—with production-readiness and scalability built in.

Our engineers migrate data, pipelines, and business logic from legacy platforms—refactoring proprietary code, validating integrity at every step, and minimizing downtime.

We validate that migrated data matches the source, train your teams on the new platform, and establish governance frameworks.

Post-launch, we provide monitoring, performance tuning, and cost optimization—scaling your platform as needs evolve toward advanced analytics and AI.

Ready to transform your data warehouse or data lake?

Pythian's related data warehouse and data lake services

From stable foundations to production AI—Pythian covers the full data journey.

Data warehouse and data lake services frequently asked questions (FAQ)

How do you ensure data security and governance during a platform migration?
We implement a robust security and governance framework from day one. This includes establishing clear policies for data access, handling, and classification, along with encryption, data catalogs, metadata management, and fine-grained access controls. During migration, we maintain strict data integrity validation and audit trails so your sensitive information is protected throughout the transition—not just after go-live.
How do you measure and ensure ROI on a data warehouse or data lake investment?
Every engagement starts with a strategic assessment that maps your platform investment to specific business outcomes—whether that's reducing total cost of ownership, accelerating time-to-insight, or enabling new analytics and AI capabilities. We track quantifiable milestones throughout delivery, and our post-launch optimization services ensure your platform continues to deliver value as your data volumes and business needs evolve.
What's the difference between a data warehouse and a data lake, and which one do I need?
A data warehouse stores structured, processed data optimized for business intelligence and reporting. A data lake stores all types of data—structured, semi-structured, and unstructured—in its raw format, making it ideal for data exploration, data science, and machine learning. Many organizations benefit from both, often converging on a "lakehouse" architecture. Pythian provides vendor-neutral guidance to help you choose the right approach based on your workloads, analytics goals, and budget—not on platform vendor preferences.
Can you help us modernize without migrating to a completely new platform?
Absolutely. Not every modernization requires a full platform migration. For many organizations, the right move is to optimize, tune, and harden governance on their current platform—especially for modern environments like Snowflake or Databricks that are scaling, not sunsetting. Pythian meets you where you are and helps you get more value from what you've already built, whether that means optimizing performance, reducing costs, or maturing your data engineering practices.
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