Unify data, analytics and AI on one governed Lakehouse. Zion brings the engineering to connect your systems, modernize your data platform and turn trusted data into everyday decisions.
A team built around Databricks
Data engineering through AI
Architecture and best practices
Proven delivery in Illinois
DATABRICKS IN PRACTICE
A connected platform for data engineering, governance, analytics and AI,
built on open formats and designed for production.
A clear starting point
Target architecture, workspace topology, network and security baselines, and a roadmap tied to measurable outcomes.
Architecture · Workspaces · Roadmap
A path off legacy
Move Teradata, Oracle, SQL Server and Hadoop workloads to Databricks with Lakebridge-assisted conversion and reconciliation.
Teradata · Oracle · SQL Server · Hadoop
Reliable data in motion
Batch and streaming ingestion, declarative transformations, data quality expectations and orchestration.
Batch · Streaming · Quality
Control across the estate
Metastore design, access policies, lineage, auditing and migration from legacy Hive metastores.
Access · Lineage · Auditing
Answers for the business
Databricks SQL warehouses, AI/BI dashboards and Genie spaces that let business users ask questions in plain language.
SQL · AI/BI · Genie
Value beyond go-live
Workspace administration, cluster policies, serverless adoption, monitoring and cost controls aligned to budget.
DataOps · Serverless · FinOps
We’ve delivered Databricks for Midwestern States
public sector programs, where data is sensitive, audit trails are required and every decision has to stand up to scrutiny.
That experience is built into how we design, govern and operate every platform.
Fine-grained, attribute-based access for PII and regulated records.
End-to-end lineage and audit logs that support oversight and compliance.
Cost visibility and controls aligned to program and fiscal-year budgets.
Built on a governed foundation.
Operated for value, not just uptime.
Inventory sources, workloads, costs and skills. Identify the priority use case and the fastest path to value on Databricks.
Design workspaces, Unity Catalog structure, medallion layers, security baselines and the governance model.
Convert legacy code, build Lakeflow pipelines and reconcile results against the source before cutover.
Run the platform with DataOps, monitoring, cost controls and enablement so adoption keeps growing.
A standing Databricks team with repeatable methods, not a bench of generalists.
Databricks-certified engineers and architects who have built for production.
Direct alignment with Databricks on architecture, best practices and program access.
Databricks on Google Cloud, Azure or AWS, integrated with the platforms you already run.
Proven in Midwestern States, with governance and accountability built into the design.
Serverless, cluster policies and FinOps practices that keep spend predictable.
