Data Engineering & Analytics
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Data Engineering & Analytics

Modern data infrastructure that makes your data actually usable at any scale.

Turn raw data into actionable insights modern data platforms, pipelines, and BI solutions built for scale.

Veritaz Data Engineering & Analytics helps Swedish organisations build the data infrastructure that powers better decisions. We design and implement modern data platforms from cloud data warehouses and real-time streaming pipelines to semantic layers and business intelligence dashboards. Our data engineers have experience across the full modern data stack: dbt, Snowflake, Databricks, Kafka, and leading BI platforms. We don't just move data we make it trustworthy, documented, and useful.

Key Benefits

  • Single source of truth for your business metrics
  • Real-time data availability for operational decisions
  • Reduce data engineering backlog with self-serve analytics
  • Data quality monitoring and alerting built in
  • GDPR-compliant data governance from the ground up
  • Scalable architecture that grows with your data volume

What's Included

Data platform architecture
ETL/ELT pipeline development
Real-time streaming (Kafka, Flink)
Business intelligence & dashboards

Our Process

A clear, structured approach from first conversation to delivery.

1

Data Audit & Architecture

We map your existing data sources, assess quality and availability, and design a target data architecture that fits your scale, budget, and team capabilities.

2

Platform Build

We build the foundational data platform cloud data warehouse, ingestion pipelines, data lake setup, and access control framework.

3

Transformation Layer

We implement the transformation layer using dbt building documented, tested data models that create a reliable semantic layer for analytics.

4

BI & Dashboards

We build dashboards and self-serve analytics in your chosen BI tool Metabase, Looker, Power BI, or Tableau designed for the business users who will actually use them.

5

Data Governance

We implement data cataloguing, lineage tracking, quality checks, and access control policies to ensure your data platform is trustworthy and compliant.

Technologies & Tools

dbtSnowflakeDatabricksBigQueryRedshiftApache KafkaApache FlinkAirbyteFivetranApache SparkMetabaseLookerPower BITableauGreat Expectations

Frequently Asked Questions

Should we use a data warehouse or a data lake?
Modern data platforms typically use a lakehouse architecture combining the flexibility of a data lake with the query performance of a warehouse. The right choice depends on your data volume, query patterns, and team skills. We help you evaluate the options.
How long does it take to build a data platform?
A foundational data platform (ingestion, warehouse, basic dashboards) can be built in 8–12 weeks. More complex platforms with real-time streaming and comprehensive data governance take 4–6 months.
Can you integrate with our existing BI tool?
Yes. We work with all major BI platforms: Power BI, Tableau, Looker, Metabase, and others. We focus on building the right data model underneath so any BI tool can query it reliably.

Ready to get started?

Talk to our team about how Data Engineering & Analytics can help your business.

Build Your Data Platform