Align your data infrastructure with what the business is actually trying to do.
Engineering-first data strategy for organizations that have outgrown their warehouse, inherited a tangle of legacy pipelines, or want to be AI-ready without burning two years on a replatform. We audit what you have, design what you need, and sequence the path between them.
Six pillars of a credible data strategy
We don't deliver a 60-slide PDF and disappear. Every engagement is anchored in code, data models, and a roadmap your engineering team can actually execute.
Legacy System Audit
We map your current data estate — warehouses, lakes, OLTP systems, spreadsheets, and shadow pipelines — and surface the gaps that quietly cost the business money: duplicated sources of truth, brittle ETL, undocumented transformations, and unreliable metrics.
Target-State Architecture
We design the data architecture you should be operating in 18–36 months: lakehouse vs warehouse, batch vs streaming, governance model, semantic layer, and the platform decisions that determine cost, agility, and AI-readiness.
Migration & Modernization Roadmap
A sequenced plan to get from where you are to where you need to be — phased migrations, parallel-run safeguards, and clear decommission criteria. No big-bang rewrites.
Data Platform Selection
Vendor-agnostic recommendations across Snowflake, Databricks, BigQuery, Redshift, Fabric, and open lakehouse stacks. We pick on workload fit and TCO — not on what's trending.
Governance, Quality & Compliance
Data contracts, lineage, observability, access controls, and the policies that make GDPR, SOC 2, and HIPAA audits boring instead of expensive.
AI & Analytics Readiness
Most AI projects fail because of the data layer, not the model. We get your foundations into a state where ML, forecasting, and LLM use-cases can actually ship to production.
From discovery to delivery in three phases
Stakeholder interviews, system inventory, data-flow mapping, cost analysis of the current stack, and a written assessment of risks, blockers, and quick wins.
Target-state design across storage, compute, ingestion, transformation, governance, and BI/ML serving. Sequenced 12–24 month roadmap with cost models and clear milestones.
We can hand the roadmap to your team, or stay on as embedded engineering partners to build the pipelines, platform, and governance described in the plan.