Slow warehouses and ageing ETL tools hold back reporting and AI. OrchV migrates and modernises data platforms, rebuilds the pipelines and puts governance in place, so the numbers agree across the business.
Reports take too long. Numbers disagree between teams. The warehouse costs more every year, and the ETL tool nobody wants to touch decides what you can change. AI projects stall because the data underneath is not ready.
We connect your data sources, engineer and govern your data, and deliver trusted, actionable intelligence to the people and systems that need it.
PostgreSQL
Excel
Hadoop
SQL Server
amazon S3
MySQL.
Azure
Hadoop
BigQueryAzure
snowflakeamazon S3Assess data maturity and plan a practical roadmap.
Bring together data from ERP, CRM, databases and SaaS applications.
Build and migrate pipelines with Azure Data Factory, PySpark and SQL, and move off ageing ETL tools.
Design platforms on Snowflake, Databricks, Azure Synapse and other cloud platforms.
Move legacy and large-scale warehouses in planned waves, validated before cutover.
Build Power BI models and dashboards, and migrate from tools such as Tableau and Domo.
Set up validation, lineage, access control and master-data practices.
Prepare clean, governed data for machine learning and AI.
A data warehouse stores structured, curated data for fast reporting. A lakehouse combines the low-cost storage of a data lake with the reliability and query performance of a warehouse, so one platform can serve reporting, data science and AI.
Yes. We migrate in planned waves, validate each wave against the source before cutover, and run old and new in parallel where needed to limit disruption.
Yes. We have migrated Informatica pipelines to Databricks and Spark for a global healthcare and life sciences organisation, which lowered ETL licence cost and made the pipelines easier to scale.
We build validation checks into each pipeline. Records that fail a check are held back for review, so the main data flow keeps running.
It depends on scope. A single pipeline or proof of value is a matter of weeks. A full warehouse migration runs in phases over several months. We agree the plan with you after an initial assessment.
Yes. We hand over documentation, data dictionaries and runbooks, and run knowledge-transfer sessions with your engineers. We can also support the platform if you prefer.
We build in role-based access, masking of sensitive fields, lineage and audit logging, designed around your regulatory requirements.
Talk to an engineer about your warehouse, pipelines or reporting.