Case Study
Revolutionizing Data Management for a Canadian Frozen Food Retail Chain:
A Journey from Chaos to Clarity
Case Study
Revolutionizing Data Management for a Canadian Frozen Food Retail Chain:
A Journey from Chaos to Clarity
About the client
The client is a Canadian frozen food retail chain located in all ten provinces, the Yukon, and the Northwest Territories.
The company specializes in selling frozen and ready-to-eat food products.
Key Outcome
As a result of this project, the customer had a working Proof of Concept of getting the data from their sources (S3, MSSQL, ElasticSearch, and Erply API) into Snowflake using Airbyte and Azure Durable Functions, then using dbt to transform the data through different modeling layers until we produced an Analyzed layer where it was ready to be queried by the visualization tool.
About the client
The client is a Canadian frozen food retail chain located in all ten provinces, the Yukon, and the Northwest Territories.
The company specializes in selling frozen and ready-to-eat food products.
Key Outcome
As a result of this project, the customer had a working Proof of Concept of getting the data from their sources (S3, MSSQL, ElasticSearch, and Erply API) into Snowflake using Airbyte and Azure Durable Functions, then using dbt to transform the data through different modeling layers until we produced an Analyzed layer where it was ready to be queried by the visualization tool.
What was their key challenge?
Key challenges of the customer were:- The data infrastructure and structure were old, it was difficult to understand and use the data, and the queries took a long time to run.
- The customer did not have the experience to design the solution and implement the migration.
- No precise data model resulted in wide tables, which are challenging to modify and maintain
- Custom scripts running inside the old Data Warehouse that performed data ingestion became hard to maintain and scale
What was their key challenge?
Key challenges of the customer were:- The data infrastructure and structure were old, it was difficult to understand and use the data, and the queries took a long time to run.
- The customer did not have the experience to design the solution and implement the migration.
- No precise data model resulted in wide tables, which are challenging to modify and maintain
Custom scripts running inside the old Data Warehouse that performed data ingestion became hard to maintain and scale
How Infostrux helped
The team had discovery meetings to understand the current status and the requirements for the solution. The best approach was to implement a ready-made Infostrux solution, Zero-to-Dashboard.
This approach included ingesting the data into Snowflake and modeling the data in a star schema so the data would be accessible in a performant way by the Visualization tool. The team implemented DEV, QA, and Production environments and a CICD pipeline for incremental data loading.
We upskilled the customer's team by establishing modern DataOps practices and managing infrastructure using IaaC to increase the delivery and reliability of the Data Platform.
How Infostrux helped
The team had discovery meetings to understand the current status and the requirements for the solution. The best approach was to implement a ready-made Infostrux solution, Zero-to-Dashboard.
This approach included ingesting the data into Snowflake and modeling the data in a star schema so the data would be accessible in a performant way by the Visualization tool. The team implemented DEV, QA, and Production environments and a CICD pipeline for incremental data loading.
We upskilled the customer's team by establishing modern DataOps practices and managing infrastructure using IaaC to increase the delivery and reliability of the Data Platform.
Conclusion
In conclusion, this case study illuminates the remarkable journey of retail client who, through the integration of cutting-edge technology and expert guidance, successfully overcame complex data infrastructure challenges.
The transition from outdated data structures to a streamlined, efficient data ecosystem demonstrates the power of innovative solutions and collaborative efforts, highlighting the transformative potential of modern data management practices for businesses seeking to enhance data accessibility and reliability.
Conclusion
In conclusion, this case study illuminates the remarkable journey of retail client who, through the integration of cutting-edge technology and expert guidance, successfully overcame complex data infrastructure challenges.
The transition from outdated data structures to a streamlined, efficient data ecosystem demonstrates the power of innovative solutions and collaborative efforts, highlighting the transformative potential of modern data management practices for businesses seeking to enhance data accessibility and reliability.
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