Client Description

Bed Bath & Beyond Inc. operates a nationwide chain of retail stores. The Company, through its retail stores, sells a wide assortment of merchandise principally including domestic merchandise and home furnishings, as well as food, gift-ware, health and beauty care items, and infant and toddler merchandise.

Bed Bath & Beyond (BBB) is the nation’s #1 superstore domestics retailer with more than 1,540 BBB stores throughout the US, Puerto Rico, and Canada. The stores’ floor-to-ceiling shelves stock better-quality (brand-name and private-label) goods in two main categories: domestics (bed linens, bathroom and kitchen items) and home furnishings (cookware and cutlery, small household appliances, picture frames, and more). BBB also operates more than 275 Cost Plus and World Market stores, and three smaller specialty chains: about 80 Christmas Tree Shops; 115 buybuy BABY stores; and more than 50 Harmon discount health and beauty shops.

Beyond its main BBB-branded chain of more than 1,540 stores, the retailer operates more than 275 stores under the names World Market, Cost Plus World Market, and World Market Stores banners. It also operates 115 buybuy BABY shops, almost 80 Christmas Tree Shops, and more than 50 stores under the names Harmon and Harmon Face Values. In Mexico, BBB also has a joint venture with Mexican retailer Home & More, where it currently operates seven stores under the BBB banner.


Bed Bath & Beyond kicked off two big-data initiatives. The first business case was to bring in clickstream Omniture data from Adobe into the data warehouse so that the customer analytics team could understand online behavior tied to their website. In the existing state, the data was sent on request by Adobe which led to long delays in data acquisition. Secondly, the warehouse team required a platform to house low latency and seldom queried data that was clogging up their existing Netezza and Teradata systems.


iOLAP architected a solution to build out a Hortonworks Hadoop cluster to serve as a data lake and ingestion platform for incoming enterprise data. Hive was utilized to store daily clickstream data which was then parsed and sent to Netezza. Using Netezza UDFs, the clickstream data was further parsed into data that could be tied to customer activity around college searches, product and event lists, and visitor keywords. Further, Hadoop’s HDFS was leveraged as an archival location for the data that was no longer required to exist on Teradata and Netezza.


Leveraging Hadoop, Bed Bath & Beyond enabled the ability to analyze clickstream data as well as laid the groundwork for a cheap storage alternative in the form of a data lake.

  • Tools: Hive | Hortonworks | Netezza
  • Categories: Analytics, Big Data, Hadoop, Strategy
  • Tags: Retail