Client: Global Quick Service Restaurant Chain Conglomerate
Situation: Management reporting was excel based and inaccurate. Lots of frustration over the “numbers”. Technology footprint was showing its age. Too much delay in getting information from over 16,000 restaurants worldwide.
Result: GBI modernized the data infrastructure and created a management-run business intelligence system. Now information trickles in from over 16,000 restaurants worldwide into one central warehouse where it is analysed and reported on. Users can create reports and analyses. The solution created substantial cost savings and massive improvement in information quality and availability.
The overall data warehouse and BI infrastructure was showing its age. Reporting inefficiencies were easily apparent. With over 16,000 restaurants reporting data, the management reporting problem became even bigger. The CIO was tasked with making changes very rapidly. Specifically …
Management reporting not accurate and based on Excel
The legacy data warehouse was showing its signs of aging
Data-marts were becoming rampant
Performance was slow and technology footprint was dated
More IT resources spent on managing infrastructure than creating value
GBI successfully delivered the Enterprise Data Warehouse and Business Intelligence Solution to our client. Using an “Agile BI” and iterative approach, GBI was able to deliver high quality results very rapidly. For the first time, the client was able to see data with hours vs. days and also experience the joys of users driving BI versus IT. The project was involved over 100 TB of data.
First data mart is rolled out to marketing in just 3 months!
Restaurant data (16,000+ restaurants) from around the world comes into the warehouse within two hours!
Executive Scorecard is redesigned and updated with live data multiple times a day (vs. once a day with yesterday’s data).
A Master Data Solution now provides most of the “gold copy” data.
Analytics are now user-driven!
Tableau for Dashboards and Analysts’ Visual Analysis
Netezza Appliance for the Data Warehouse
SAP Business Objects for Reporting
Informatica for Data Movement and Cleansing
Source databases consist of MySQL, SQL Server, and Oracle
Other Related Facts
Duration: June 2012 – Present (ongoing). All projects have been run in an Agile fashion with the average iteration duration of 1 week.
Team Size: 10-20 depending on size of deliverable.
Data Facts: 100+ TB of storage; 5.7 Million rows / hour; data cleansed and transformed in real-time.
Data Warehouse Footprint: 7 years of data detailed data with a BI layer on top which allows end users to report on their own.