Scalable Cloud Analytics Infrastructure for Real-Time Insights

Scalable Cloud Analytics Infrastructure for Real-Time Insights

Overview

Euvic partnered with a leading enterprise to overhaul its analytics infrastructure, transitioning from on-premise systems to a scalable, high-performance cloud solution. This enabled the client to handle large datasets and deliver real-time, actionable insights for decision-making. 

Client

A global organization with operations spanning multiple regions, focused on enhancing analytics capabilities to drive business decisions.

Industry
Technology and Analytics
Country
Finland

Flexibility was a big selling point for us. We are collaborative, and prefer to be flexible. Euvic demonstrated time and again that they could adapt to our working norms, collaborate across cultures, and give us exactly the engineering talent that we needed.

Orcun Uzun
CEO, Tikla Gelsin
Background
Challenge

The client faced several pressing challenges: 

  • Scalability limitations: The rapidly growing data warehouse exceeded the capabilities of the existing on-premise infrastructure. 
  • Performance bottlenecks: Slow data processing impacted the timeliness of insights. 
  • Transition requirements: The need to migrate to a cloud-based solution while minimizing disruptions. 
Solution

Euvic delivered a comprehensive solution to address these issues: 

  • Cloud migration: Transitioned the client’s data warehouse to Azure, improving system scalability and performance. 
  • Data integration: Streamlined data extraction and transformation using Azure Data Factory. 
  • Advanced reporting: Developed a semantic model with Azure Analysis Services to enable efficient and detailed reporting. 
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Technology Overview
Technology
Microsoft Fabric
Power BI
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Technology
The Dream Team
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Results

The project delivered significant business-specific benefits: 

  • Improved scalability: Seamlessly handled large datasets, enabling future growth. 
  • Enhanced performance: Reduced time-to-insight, accelerating business decisions. 
  • Cost optimization: Lowered operational costs with a more efficient cloud infrastructure. 
  • Real-time analytics: Provided timely insights to support critical decision-making processes. 

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