The data layer that actually serves the business.
Data modernization, Customer 360, MLOps, and analytics platforms on Snowflake, Databricks, and the hyperscalers — turning fragmented information into reliable insight, governed properly, with the pipelines your team can own.
Most leadership dashboards are polite fiction.
The data lives in twelve systems. The pipelines run on someone's laptop. The definitions of "active customer" disagree between Sales and Finance. The dashboard refreshes nightly except when it doesn't. And every quarter, the leadership team makes consequential decisions based on numbers nobody fully trusts.
PEXIVA Data exists to fix that. Modern data platforms with governance built in, Customer 360 architectures that actually unify customer data across systems, MLOps pipelines that ship models reliably, and analytics platforms whose insights leadership can trust. Reliable, governed, and yours to operate.
Why Data Programs Stall
Five patterns that defeat most enterprise data initiatives.
- No common definitions across systems or teams
- Pipelines built without observability or lineage
- Governance bolted on after launch (too late)
- Tooling sprawl — five tools doing similar jobs
- Operations handed back to a team without runbooks
From raw data to reliable decision.
PEXIVA Data covers the full lifecycle — modernization, integration, analytics, MLOps, and governance — on the platforms that actually serve mid-market reality.
Data Platform Modernization
Migrate from legacy data warehouses, on-prem ETL, and SaaS sprawl to a modern stack on Snowflake, Databricks, or hyperscaler-native platforms. Phased, risk-managed, with golden-record migration patterns and parallel-run validation before cutover.
Customer 360 & Identity Resolution
Unify customer data across CRM, marketing, support, billing, and operational systems into a single source of truth. Identity resolution, golden record management, real-time updates, and the privacy controls that keep regulators satisfied.
Analytics & Leadership Dashboards
Reliable BI platforms — Tableau, Power BI, Looker, ThoughtSpot — built on top of governed semantic layers. KPIs that everyone agrees on, dashboards leadership trusts, and a self-service tier for analysts that doesn't break governance.
Modern Data Engineering
Pipelines built with observability, testing, and lineage as first-class concerns. dbt, Airflow, Dagster, Fivetran, and Spark — selected for the workload, not the trend. Operations team trained before handoff, runbooks delivered with the code.
ML Platforms & MLOps Pipelines
End-to-end MLOps for traditional ML — feature stores, model registry, training pipelines, evaluation, deployment, monitoring, drift detection, and retraining. SageMaker, Vertex AI, Databricks ML, or open-source toolchains based on your stack.
Data Governance, Lineage, & Privacy
Governance frameworks that work in practice — catalogs, lineage tracking, data quality monitoring, privacy classifications, and access controls. Mapped to HIPAA, SOC 2, GDPR, and state privacy laws. Designed for adoption, not shelfware.
Bring us a dashboard nobody fully trusts.
Or a CRM that disagrees with your finance system. Or a data team that's drowning in pipelines. Or a Customer 360 initiative that's been stuck in design for a year. Free 1-hour data diagnostic — we'll come prepared.