Veolia Umweltservice GmbH – Building a Cloud DWH
For Veolia, cimt optimised the ETL processes of a cloud DWH on Google BigQuery with Talend – recognised with the Talend Data Masters Award 2022.
Data warehouse consulting
Data Warehouse Consulting for Modern, Open ArchitecturesCloud, on-premises or hybrid
From data strategy to a productive platform: we work with you to design the data warehouse architecture that fits your data, your budget and your compliance requirements – strong on governance, auditable and scalable.
Data Vault 2.0
auditable data models
Qlik Elite
partner for data integration
Snowflake & Databricks
partner for cloud DWH
ISO 27001
certified information security
Challenge
The reality of modern data architectures
Modern data warehouse consulting does not start with the tool, but with your goals. We combine proven DWH principles with open, cloud-native architectures – for example with Snowflake, Databricks, Qlik Talend and dbt. The result is a data platform that scales, remains auditable and delivers real value to the business. For the bigger picture, see our data & analytics services.
Three hurdles slow down data-driven projects – regardless of industry and tooling:
Data silos and fragmented sources
Distributed systems, inconsistent definitions, no single point of truth – reports contradict each other.
Scale and cost
Growing data volumes drive up costs, while rigid architectures slow down time to insight.
Governance and auditability
Missing lineage and incomplete evidence turn compliance and audits into a risk.
Architecture
Architecture approaches for your data warehouse
Depending on your data strategy, toolset and business requirements, we choose the right model together – independently of any vendor.
Classic core DWH
Stable ETL pipelines, high data quality and proven BI structures for long-term reporting requirements.
Data Vault 2.0
Historised, auditable and agile to extend – ideal for compliance and growing source systems.
Cloud lakehouse
Open formats such as Apache Iceberg, SQL and machine learning in one platform – with Snowflake or Databricks.
Hybrid architecture
On-premises and cloud combined – for step-by-step migration and compliant workloads.
Logical DWH
Real-time data virtualisation without physical replication – for example with Denodo.
Streaming and Kappa
Real-time pipelines instead of batch – with Kafka and Confluent for IoT, logistics and fraud detection.
Use cases
Typical use cases
From group reporting to an AI foundation – this is what organisations achieve with modern data warehouse architectures.
Central group reporting
Consistent KPI reports and self-service analytics with Qlik, Power BI or Tableau on a consolidated data basis.
Self-service BI and data products
Business teams access reusable data products in a governed way – without an IT bottleneck.
Master data and MDM
Centrally maintained master data for e-commerce, production and CRM – distributed automatically.
Real-time and IoT analytics
Streaming pipelines for logistics, IoT and customer service – analyse events in real time.
Replacing SAP BW
Replace BW on HANA with Snowflake or Databricks – without losing reports and at lower operating costs.
Foundation for ML and AI
A clean data platform as the basis for machine learning, forecasting and agentic AI.
Technology
Technologies and focus topics
We are technology-agnostic and choose the right platform for your requirements. For AI-powered analytics, we rely on Qlik – combined with Qlik Talend for robust data integration. As a Qlik Elite Partner, Snowflake Select Partner and Databricks partner, we know these platforms from practice. We cover these topics in depth on dedicated pages:
Data lakehouse strategy
Assess lakehouse architectures and develop a future-proof data strategy – with our workbook (in German).
Data Vault modelling
Historised, audit-proof DWH models with Data Vault 2.0.
Data integration with Qlik Talend
Robust ETL and ELT integration with Qlik Talend – from cimt as a Qlik Elite Partner.
Data governance and data catalog
Transparent data flows and consistent terminology with Collibra or Alation.
Snowflake
Building cloud data warehouses and architecture consulting around Snowflake.
Databricks
Lakehouse, data engineering and AI on the Databricks platform.
Case studies
Data platform projects in practice
OTTO – Big Data Analytics
For OTTO, cimt built a platform based on big data technologies for developing and operating analytical models.
Generali – Generic Data Integration
For Generali, cimt implemented the Talend data integration of the group-wide data platform – from generic ETL strategy to test automation.
FAQ
Frequently asked questions about data warehouse consulting
Cloud, on-premises or hybrid – which data warehouse architecture is right for us?
That depends on your data strategy, compliance requirements and existing toolset. We assess the options neutrally and recommend the architecture that fits your goals – from a classic core DWH through Data Vault to a cloud lakehouse.
Is a lakehouse with Snowflake or Databricks worth it compared with a classic DWH?
Often yes – especially for large, diverse data volumes, ML workloads and cost optimisation via open formats such as Apache Iceberg. We compare both approaches for your case and calculate the potential savings. More in our article Replacing SAP BW on HANA: Snowflake or Databricks?
We already use Power BI, Tableau or SAP BW. Can we work with cimt?
Yes. Our services – architecture, integration, governance and data quality – are technology-neutral. cimt is a Qlik Elite Partner, Snowflake Select Partner and Databricks partner, but works seamlessly with the toolset you already use.
Which technologies does cimt use for data warehousing?
Among others, Databricks, Snowflake and Qlik Talend for platform and integration, dbt for transformation, and Collibra, Alation for governance and data catalogs. For analytics and AI-powered insights, we rely on Qlik.
How does a data warehouse project with cimt work?
Usually with a no-obligation strategy call, followed by a compact architecture assessment. This results in a prioritised roadmap – and we support you from the first decision through to productive, auditable operation.
How does cimt ensure governance, auditability and compliance?
Through audit-proof models such as Data Vault, end-to-end lineage and a data catalog such as Collibra or Alation, plus clear ownership structures – so your data stays traceable, verified and compliant.
Contact
Let’s talk about your data warehouse
Are you planning a new data warehouse, want to replace SAP BW or have an existing platform reviewed? We will get back to you promptly for a free initial consultation.
Contact person
Your contact
Rouven HomannMember of the Executive Board, cimt Group
Note: This text was created or revised with the support of AI.