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Headquartered in Bentonville, Arkansas, this company Walmart be it in the in-store purchases or social mentions or any other online activity, Walmart has always been one of the best retailers in the world.
American multinational retail giant Walmart collects 2.5 petabytes of unstructured data from 1 million customers every hour. One petabyte is equivalent to 20 million filing cabinets; worth of text or one quadrillion bytes. The data generated by Walmart every hour is equivalent to 167 times the books in America’s Library of Congress. With tons of unstructured data being generated every hour, Walmart is improving its operational efficiency by leveraging big data analytics. Walmart has created value with big data and it is no secret how Walmart became successful.
- Proper scaling
The supreme quality of Walmart is its scaling. Scale in terms of customers, products and technology. Walmart makes $36 million dollars from across 4300 retail stores in US, daily and employs close to 2 million people.
- Making Walmart pharmacies more efficient
Walmart uses simulations at the pharmacy to find out many prescriptions are filled in a day and to determine the busiest times during a day or month.
- Social Media Big data solutions
A big part of Walmart’s data driven decision are based on social media data- Facebook comments, Pinterest pins, Twitter Tweets, LinkedIn shares and so on. Walmart Labs is leveraging social medial analytics to generate retail related big data insights. Walmart collects 2.5 petabytes of unstructured data from 1 million customers every year. Not only this, Walmart gives mobile data solutions also.
- To manage the supply chain
The company uses simulations to track the number of steps from the dock to the store. The result: more optimized routes to the shipping dock. The strategy also pinpoints the number of times a product gets touched along the way to the customer. Big data also reveals transportation lanes and routes for the company’s fleet of trucks. This insight helps Walmart keep transportation costs down and more accurately schedule driver times, according to the blog.
- To personalize the shopping experience
By analyzing shopper’s preferences, Walmart can develop a more consistent, tailored shopping experience. If a customer is shopping for baby products for example, Walmart can use data analytics to anticipate their needs then create personalized mobile rollback deals for these shoppers.
Walmart has a broad big data ecosystem. The big data ecosystem at Walmart processes multiple Terabytes of new data and petabytes of historical data every day. The analysis covers millions of products and 100’s of millions customers from different sources.
“Our ability to pull data together is unmatched”- said Walmart CEO Bill Simon. A familiar example of effective data mining through association rule learning technique at Walmart is – finding that Strawberry pop-tarts sales increased by 7 times before a Hurricane. After Walmart identified this association between Hurricane and Strawberry pop-tarts through data mining, it places all the Strawberry pop-tarts at the checkouts before a hurricane.
But,the biggest challenge for retailers like Walmart is to make predictions with limited historical data.