Driving Growth with Cloud Transformation and Modern Dashboards
Driving Growth with Cloud Transformation and Modern Dashboards
Overview
Euvic facilitated the client’s migration to a scalable, cloud-based infrastructure, addressing inefficiencies in their legacy systems and introducing modern reporting tools. The project empowered the client to leverage advanced analytics, optimize costs, and achieve better performance across its operations.
Client
A mid-sized enterprise undergoing digital transformation for market expansion. The client’s outdated systems were becoming a barrier to growth, prompting a need for a comprehensive overhaul.
Industry
Retail and E-commerce
Country
Sweden
Background
Challenge
The organization’s existing systems faced significant limitations:
- Costly infrastructure: High expenses for on-premise data systems strained budgets without delivering proportional value.
- Outdated tools: Legacy QlikView dashboards lacked flexibility and failed to meet modern reporting requirements.
- Performance issues: Existing infrastructure slowed data processing, limiting the ability to scale operations and explore new markets.
Solution
Euvic’s cloud-focused approach addressed these challenges:
- Azure Databricks integration: Deployed Apache Spark to enhance data processing efficiency and enable large-scale analytics.
- Data pipelines: Built robust pipelines using DBT scripts, storing data in Azure Data Lake to ensure reliable and flexible data management.
- PowerBI upgrade: Replaced legacy dashboards with dynamic PowerBI solutions, offering user-friendly interfaces and advanced visualization capabilities.
- Custom analytics models: Designed models tailored to the client’s specific reporting and forecasting needs, including market expansion analysis.
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Technology Overview
Technology
Databricks
Azure Data Lake
Power BI
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Technology
The Dream Team
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Results
The transformation yielded significant outcomes:
- Scalable architecture: Supported seamless expansion into new markets by providing the agility needed for rapid growth.
- Unified data model: Enabled comprehensive analytics and AI-driven insights, enhancing operational efficiency.
- Improved efficiency: Delivered faster, more reliable access to analytics tools, enabling employees to make informed decisions.
- Cost optimization: Reduced infrastructure and operational costs while improving system performance.
