What challenges did PERI SE face before AI implementation?

SAP BW on HANA struggled to meet growing demands for real-time analytics, data availability, transparency, and cost-efficient scalability. Business units needed faster self-service analytics and a future-proof foundation for AI and advanced analytics.

What was the impact of the AI solution?

PERI reduced time-to-insight for new reporting use cases from about 3-4 days to about 1 day. The new architecture streamlined data pipelines from more than five steps to one or two stages. The platform enabled advanced AI and machine learning scenarios for real-time decision-making.

Source

Microsoft

PERI accelerates time-to-insight and enables AI-ready analytics with Microsoft Fabric and Azure Databricks

Use case typeData platform modernizationUpdated Jun 23, 2026

PERI SE modernized its analytics landscape from SAP BW on HANA to a Lakehouse-first architecture built on Microsoft Fabric and Azure Databricks. The new platform uses OneLake as a unified data foundation, Medallion (Bronze/Silver/Gold) processing, and Power BI Direct Lake for self-service analytics with governance. The implementation also introduced CI/CD with Azure DevOps and Infrastructure as Code with Terraform through partner b.telligent.

Organization: PERI SE
Industry: Manufacturing
Location: Germany
Published: June 2026

Reported outcomes

3 days to 1 day

time-to-insight for new reporting use casesTime & speed

−60%data pipeline stages

Strategic outcomes

Better decisions & insightFaster decision-making from curated analyticsBetter decisions & insightCreated an AI-ready analytics foundation

Primary read

Use case focus

Showing 2 of 2

1Data platform modernization
2Real-time analytics

SAP BW on HANA struggled to meet growing demands for real-time analytics, data availability, transparency, and cost-efficient scalability.
Business units needed faster self-service analytics and a future-proof foundation for AI and advanced analytics.

Migrate analytics from SAP BW on HANA to a Lakehouse-first architecture on Microsoft Fabric and Azure Databricks.
Use OneLake as a standardized enterprise data foundation with Medallion-based processing for structured data preparation.
Enable self-service reporting through Power BI with Direct Lake while maintaining governance.
Implement CI/CD with Azure DevOps and Infrastructure as Code with Terraform to make the platform reproducible and sustainable.

Technologies

Microsoft Fabric OneLake Azure Databricks Power BI Azure DevOps Terraform

PERI reduced time-to-insight for new reporting use cases from about 3-4 days to about 1 day.
The new architecture streamlined data pipelines from more than five steps to one or two stages.
The platform enabled advanced AI and machine learning scenarios for real-time decision-making.

Architecture

The solution is a Lakehouse-first architecture on Microsoft Fabric and Azure Databricks. OneLake provides a single data foundation, data is processed through a Bronze/Silver/Gold Medallion pattern, Power BI Direct Lake serves curated data for self-service analytics, and Azure DevOps plus Terraform support CI/CD and infrastructure as code.

Implementation partners1

b.telligent

Sources & evidence1

Groundedness: 5/5Type: Customer StoryPublished: Jun 23, 2026Publisher: MicrosoftEvidence: PrimaryConfidence: High

Primary source

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