American Tire Distributors
🧠 How a Data Fabric Gets Snow Tires to a Store When You Need Them
“We were losing sales because the store owners were unable to answer the customers’ questions as to when exactly they would have the product in stock,” said Ehrar Jameel, director of data and analytics at ATD. The company didn’t want frustrated customers looking elsewhere. So he wanted to create what he called a “supply chain control tower” for data just like the ones at the airport.
“I wanted to give a single vision, a single pane of glass for the business, to just put in a SKU number and be able to see where that product is in the whole supply chain —not just the supply chain, but in the whole value chain of the company. ATD turned to Promethium, which provides a virtual data platform automating data management and governance across a distributed architecture with a combination of data fabric and self-service analytics capabilities.
It’s built on top of the open source SQL query engine Presto, which allows users to query data wherever it resides. It normalizes the data for query into an ANSI-compliant standard syntax, whether it comes from Oracle, Google BigQuery, Snowflake or wherever. It integrates with other business intelligence tools such as Tableau and can be used to create data pipelines. It uses natural language processing and artificial intelligence plus something it calls a “reasoner” to figure out, based on what you asked, what you’re really trying to do and the best data to answer that question.