Technology
Data Management

Implementing a Scalable Data Engineering Platform for a Trust and Corporate Management Company

The client needed a robust data engineering platform to collate and transform data from multiple ERPs, ensuring scalability, cost-effectiveness, and the ability to incorporate micro-strategies over the data architecture.
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Challenge
Solution
The Outcome

The Challenge

The primary challenge was to create a scalable and cost-effective data engineering platform capable of integrating multiple ERPs while minimizing service delays and maintaining high performance.

Scalability and Cost Efficiency

Designing a thin and scalable data engineering layer suitable for the cloud with pay-per-use to minimize costs.

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Integration and Transformation

Handling data integration and transformation from multiple ERPs to ensure seamless data flow and accurate analytics.

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The Solution

Entrans developed a comprehensive data engineering platform with Azure architecture, integrating various technologies to achieve the client's objectives.

Result:

The platform provided efficient data integration, transformation, and storage, ensuring scalability and cost-effectiveness while supporting future growth.

Detailed Solution:

  • Azure Architecture: The solution utilized Azure architecture to provide a scalable and cost-effective platform. The use of Azure DataBricks with Spark allowed for efficient data processing, despite slower start times and non-serverless nature. The architecture separated computation from storage, with Blob storage used for data storage.
  • Curated Data Lake: The preliminary stage involved creating a curated data lake before loading data into Azure Datawarehouse. Transformations were handled in Spark, and the transformed data was then pushed into Blob storage, which synced with Azure Datawarehouse.
  • Scalable Instances: Startup times were required while running as spot instances, and instances were scaled on demand to ensure optimal performance.

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Impact:

The implementation led to a scalable, efficient, and cost-effective data engineering platform that streamlined data integration and transformation, enhancing the client's ability to make data-driven decisions.

Future-Ready Data Architecture:

‍The platform is built with extensibility at its core, supporting seamless integration of emerging Azure services and third-party data sources. The modular design allows for easy adoption of advanced analytics capabilities, machine learning models, and real-time streaming as business needs evolve, without requiring architectural overhauls.

What Our Client Says

‍"Entrans delivered a data platform that exceeded our expectations in both performance and cost efficiency. The Azure-based solution they architected has become the backbone of our analytics operations, processing terabytes of data daily while keeping costs predictable. Their expertise in optimizing Spark workflows and designing the curated data lake approach has positioned us perfectly for our next phase of growth and AI initiatives." - Chief Data Officer, Enterprise Technology Company

The Outcome

The platform provided a thin and scalable data engineering layer suitable for the cloud with pay-per-use, minimizing costs.

The platform ensured seamless data flow and accurate analytics by handling data integration and transformation from multiple ERPs.

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The platform ensured seamless data flow and accurate analytics by handling data integration and transformation from multiple ERPs.

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The architecture allowed for the addition of any micro-strategy over the data architecture, supporting future growth and scalability.

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We have been working with Entrans for the last two years and they have played a key role in building our solution. Their expertise and professionalism were evident throughout the development cycle, and we were very pleased with the final product. They have shown enormous skill and vast domain knowledge and their IT expertise is reliable and trustworthy. We would recommend Entrans for anyone looking for quality IT services, delivered in a professional manner
Nikolay Prokopiev
Chief Executive Officer
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