Automate Your ELT Processes Directly on Databricks

Traceability from raw source to final report

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Productivity Increase accross project lifecycle

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From requirement to production

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Successful Data Warehouse Automation Implementations Across Industries

All the power of Datavault Builder – now fully available on Databricks

End-to-end automation – from raw data ingestion to analytics-ready reporting, Datavault Builder automates DWH processes without endless manual coding
Out-of-the-box petterns – bi-temporality, historization and lineage come pre-built, so you don’t have to reinvent the wheel for every project
Agile delivery – deliver marts, KPIs and dashboards in small sprints, showing business value continuously instead of waiting months for results
Built-in governance – full audit trail, automated documentation and compliance-ready transparency are included by default
Trusted by business users – every business rule is traceable from source to target, giving decision-makers confidence in the data
Reduced maintenance – avoid fragile custom scripts and fragmented pipelines, lowering long-term effort and costs

Recognized for Excellence in Data Warehousing Automation

Automate Data Vault Deployment and ELT on Databricks : fast, scalable, and secure

No more custom scripts – pipelines and models are generated automatically, saving weeks of repetitive SQL or Spark coding
Cloud-native scalability – designed for Databricks and Delta Lake, performance grows seamlessly with your data
Team collaboration – data engineers, architects and analysts work in one end-to-end plattform instead of juggling separate tools
DataOps-ready – integrated Git versioning, automated testing and monitoring support professional workflows following Dev-Ops best practices
Rapid onboarding – new data sources can be integrated in a fraction of the time
Future-proof architecture – adapt quickly to new business requirements without re-factoring your pipelines and data model

Who is it for?

Data engineers

Who need streamlined ELT and modeling workflows without endless custom coding with automated documentation

Data architects

Data architects designing scalable, cloud-native Lakehouse solutions that are future-proof

BI Teams

BI teams in enterprises looking for faster, cleaner access to analytics-ready data on Databricks

Data scientists

Data scientists who need reliable, good quality data for trusted insights.

AI Innovators

AI innovators who want to build on trusted, high-quality data in platform — to have production ready, governed, maintained GenAI and AI use cases delivering ROI

Project Leads

Project leads who aim to de-risk projects and deliver results faster — with automated and governed workflows, full traceability on delivered work

Bring structured, semi-structured and unstructured data together –
fully automated in
Databricks Medallion Architecture

Any data, one platform – relational tables, JSON, IoT streams, files or logs, all integrated seamlessly
Lakehouse + Data Vault – combine Databricks’ flexibility with Datavault Builder’s structured governance
Medallion Architecture and Data Vault – Datavault Builder’s standardized workflow fits seamingsly into the Medallion Architecure
Analytics-ready output – historized, cleaned and fully governed data flows directly into BI and AI tools
No more silos –eliminate fragmented ETL pipelines across different stacks
Faster insights – shorten the time from raw data to business value

It’s confidence of the business users in the new data infrastructure and trustworthiness of data where DVB stepped in.

The documentation aspect of itis a massive bonus.

Being able to click into a business rule and just say: this is how this specific thing works from source to target. The way business rules are kept really atomic and simple has supported us in keeping people’s confidence high while building the new DWH.

Kristofer Walker

Group IM&T Business Intelligence Manager

Frequently Asked Questions

How does Datavault Builder connect to Databricks?

Datavault Builder integrates directly with Databricks as the target database. All Data Vault models and ELT pipelines are generated natively in Databricks – no middleware or extra layers required.

Do I need to adapt my existing Databricks setup?

No. Datavault Builder runs on top of your Databricks environment. It generates code that executes directly in Databricks, so you can keep your current setup.

Can I use both structured and unstructured data?

Yes. Datavault Builder handles relational data, files, JSON, IoT streams and logs. Everything can be managed and historized in one Lakehouse architecture.

What are the main benefits compared to custom pipelines?

You save time and reduce risk: instead of hand-coding, you get automation, built-in governance, lineage, documentation, and ready-to-use standards like bi-temporality.

Who benefits most from this integration?

Data engineers, data architects, and BI teams in enterprises that want to accelerate their Databricks projects without losing governance or flexibility.