Data Platform Client Story Featured

Upgrading to the Cloud for a Better Data Platform

Enter Centric: Real-Time Insights in One Central Place

While the client’s initial, on-premises data server had served their needs well for quite some time, it was due for an upgrade. Outdated analytics technology spread critical business logic and data across numerous platform components, which slowed down data processing time, limited maintenance windows, and overall, impeded client’s business operations.

The company needed our help to modernize their solution, which required migrating existing operational and analytical platforms to Azure PaaS resources. A move to the cloud would allow our client to continue to innovate and make more effective decisions through real-time, across-organization access to information.

“We knew they wanted to significantly scale, and the cloud gives them the flexibility to do that very easily,” says Senior Data Architect Jeff Aalto.

Our “re-platform” effort involved rewriting and migrating dozens of SSIS jobs to Azure Data Factory, lifting two legacy applications into Azure App Services, and supporting it with new implementations of Synapse Analytics (Azure SQL Data Warehouse), Azure Analysis Services, Azure Blob Storage and many other supporting PaaS components.

We took their existing solution and shifted them to a modern platform as a service approach that takes the maintenance away from them. We migrated their codebase from their old, on-premise location into a cloud-based implementation that improved performance and gave them a platform that can grow and evolve with the business over time.

The Results: A Fully Functional Cloud-Based System

In just a few months, we delivered a fully functional cloud-based data management platform, which resulted in a variety of benefits for our client, including:

  • A more expedient source file process, shortening process time from days to hours
  • Centralized monitoring of the overall solution with a Power BI dashboard that brings together processing data, input data validation information and data reconciliation analysis enabling users to identify issues more quickly and resolve them more efficiently
  • Consolidated and centralized business logic within the data warehouse as the single source of truth from which users can derive all downstream analytical and application sourced information, increasing supportability of the solution over time
  • Integrated data and process logging throughout the solution, significantly improving the ability to troubleshoot and resolve issues quickly and correctly
  • A higher degree of confidence in the accuracy and timeliness of data for end-users.

In summary, we provided our client with a single system that allows them to manage their data more efficiently and effectively, enabling them to improve business operations as a whole.

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