Success on the menu

Gordon Food Service (GFS) has come a long way from the days when it delivered butter and eggs to local customers. Over a century later, it’s the largest family-operated broadline food distribution company in North America.

A commitment to great products and quality service has been the recipe for success. GFS has a client base of around 100,000 customers, including schools, hospitals and restaurants.

Data can power the success of any business, but that data needs to be clear, accessible and consistent to be useful.

GFS's data was coming from a variety of consumer applications directly connected to multiple data sources drawn from both the cloud and the business premises. The result? Varying views and dependencies for database administration, causing rigidity.

GFS had a real operational need for this data, including the ability to:

• Gordon Food Service Manage pricing and promotions.

• Gordon Food Service Track historical product price changes.

• Gordon Food Service Analyze purchase behavior.

But the difficulty in accessing the numbers that mattered meant opportunities were being missed.

Our solution was to bring everything together in one place.

We created data pipelines to supply an Integrated Consumption Data Store (ICDS) that supported GFS's operational and analytical needs. In essence, everything collected flowed into one place where it could be viewed, used and analyzed to add real value for decision-makers.

The tech that powered the data modernization

Understanding the technology available and working closely with those who create it means the optimum solution can be delivered. To build the ICDS, we leveraged our long-term partnership with Google Cloud.

After careful analysis and consultation, we agreed that Google Cloud’s Dataflow would be ideal as a serverless execution engine for Apache Beam SDK to do batch data processing.

Data is extracted from BigQuery and stored in Cloud SQL. This allows GFS to achieve data syndication, speed and accessibility for various operational needs.

Faster, flexible and cost-effective

Not only does this solution save GFS money, but it can be scaled up and down when required. Data is accessed via a standardized API layer built and deployed within GKE. This takes advantage of the automated scaling and high-availability across regions and multiple zones.

Costs and resource overhead are managed on database admins, and it delivers data significantly faster while using BigQuery for limitless compute along with Dataflow for ETL processing of batch and streaming data. CI/CD automation is integrated into the data pipelines.