Situation

A major grocer captures large amounts of disparate data to support the movement and storage of goods to and from their manufacturing sites, vendors, distribution centers, and stores.  They sought to capture as much supply chain data as possible to support a broad range of data analytic projects. They needed to identify the data sources needed for these reports, develop the programs to capture the data using daily, weekly and/or monthly ETL processes, develop the four layers of data within the Hadoop clusters and provide end-users with both clean data for analytical deep dives and Business Intelligence reports.

Solution 

Ingage Partners worked with the Business Analysts to coordinate with the data source owners for access and understanding of their data. We collaborated with various teams to gain access through firewalls for FTP programs to access third-party source data. We joined the Big Data team to explain how the team was using Hadoop and to share tools available for developers and end-users. And, we coordinated with the Big Data team to support our development of the data storage and subsequent viewable data within the Hadoop infrastructure. We analyzed incoming data structures to provide insights to end-users on how best they might query the data and supported these end-users with SQL tuning.

Results 

We were able to bring in nearly all the desired data sources. Analysts now have a much greater view of the supply chain data; allowing them to improve truck routing, reduce the number of empty loads and innovate with supply chain insights.

Dev Tools