Data migration from on-prem to Snowflake cloud data warehouse
Leading supplier of fuel and one of the largest operators of travel centers
A nationwide operator of truck stops and travel centers is getting smarter about its business by accelerating the delivery of data and insights to its leadership.
Architecture & Engineering
BI Reporting & Visualizations
Build & Migrations
Business Analytics
Business Intelligence & Insights
Cloud Infrastructure Modernization
Data Management
Platform Management
Amazon S3

Data visualization services

Travel Center Operator Migrates to Cloud Data Warehouse for Accelerated Data Visualization

On-premises data warehouse causes data traffic jam  

A nationwide operator of truck stops and travel centers is getting smarter about its business by accelerating the delivery of data and insights to its leadership. 


This data-driven organization relies on hundreds of dashboards to inform decision-making in all areas, from finance to store management to logistics. But as the company and its offerings grew, so did the data volumes. The company’s on-premises data warehouse solution could no longer keep up with executives’ growing appetite for analytics.  


The data warehouse was used for both ETL and reporting purposes, which competed for resources and connections. Data ingestion performance suffered when running concurrently with analytics jobs. As a result, dashboards took longer and longer to render, and executives weren’t getting data when they needed it.  


They knew it was time to shift to a “future-ready platform” that could be used for multiple types of workloads, from data ingestion and analytics to data science and machine learning.  


Snowflake data warehouse fuels faster insights  

The company teamed up with Wavicle Data Solutions, a Snowflake partner, to evaluate cloud data warehouse solutions and then help drive the cloud migration.  


The new environment includes an AWS S3 data lake, which now houses the ETL process, and a Snowflake data warehouse, which drives reporting.  


Wavicle delivered a four-part solution that included:  

  • Proof of concept and benchmarking: A 4-week POC evaluated two cloud data warehousing platforms for their ability to run ingestion and analytical jobs concurrently, meet runtime and workload performance SLAs for big SQL queries, and improve performance of ingestion jobs. We presented findings that pointed to Snowflake as the best option when balancing cost and performance priorities.  
  • Data migration: Migration of 40 Terabytes of historical data from the cloud data lake into 400+ data warehouse tables in Snowflake, most of which are synced three to four times per day.  
  • Data ingestion: Migration of data ingestion jobs from original data warehouse into Snowflake environment.  
  • Dashboard migration: Migration of 200+ Tableau dashboards from the original data warehouse environment to Snowflake. 


New solution paves the way for fast insights and data science use cases  

By migrating to a cloud solution and separating the data ingestion and analytics jobs into different environments, this solution meets business SLAs for performance, run times, and data delivery. For example, dashboards that once took 40 minutes to render now are ready within five minutes. Across the organization, business leadership gets analytics and insights when they need it.