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Big Data Use Cases

There is nothing like knowing that some one is using this technology to bring value to their business. Even better if they have made Big Data as part of their business strategy to win over the competition.  Here are some examples for us.

Companies using Big Data

  • Company : Etsy
  • Category  : On line retailer
  • Big Data Attribute : Volume
  • Revenue: $895 M

Etsy is an online retailer for handmade and vintage items. In last few years, company has increased its sales by many times. As a big data project, they took their clickstream data and analyzed the customer actions while shopping.  Company used the intelligence learnt from click data to personalized the rank for the search results. It increased the sales.

  • Company : Macy,
  • Category  : Brick and Mortar retailer,
  • Big Data Attribute : Volume and Speed
  • Revenue: $26 B

Price check analysis of its 10,000 articles across 800 stores nationwide in less than 2 hours.  When ever a neighboring competitor between New York and Los Angles goes for aggressive price reductions, Macy’s follows the suite. If there is no competition, price remains unchanged.  There are around 270 million different prices across entire range of goods and locations.  Just completing  this analysis at this speed was unthinkable without Big Data.

  • Company : Sears Holdings (Sears and Kmart)
  • Category  : Brick and Mortar retailer
  • Big Data Attribute : Volume and Velocity
  • Revenue: $42 B

Sears’ process for analyzing marketing campaigns for loyalty club members used to take six weeks on mainframe, Teradata, and SAS servers. The new process running on Hadoop can be completed weekly. For certain online and mobile commerce scenarios, Sears can now perform daily analyses. What’s more, targeting is more granular, in some cases down to the individual customer. Whereas the old models made use of 10% of available data, the new models run on 100%.

Use cases by verticals

Here are some additional examples of big data projects by verticals. For example financial services companies are using big data technology to improve their customers insight and detect the fraud. They are even building models to predict fraud before it happens. Healthcare companies are using big data for gene sequencing.

Financial Services

  • Customers Insights – using Hadoop to improve customer profile analysis to help determine Eligibility for equity, capital, insurance, mortgage and credit
  • Fraud detection – Hadoop provides the scalable method to easily detect many
  • Types of fraud and loss prevention. Companies are also developing models to predict Future fraud events like PayPal.
  •  Micro Targeting – Banks have multiple silo systems for loans, mortgages, investments. Hadoop can be used to provide aggregated view on customer profitability.

Healthcare and Life Science

  • Health Information exchange – Hadoop can be used by providers to manage and share healthcare records from mixed data sources such as images, treatments, demographics and billing
  • Gene Sequencing – The sequencing of DNA for organism holds huge promise for human kind.


  • Service Management – The availability of sensors and corresponding ability to effectively store and analyze large data feeds across customer locations and product SKUs, has resulted in more effective and efficient service.
  • Operations – Hadoop can also improve the post sales maintenance process. The manufacturing industry is adding sensors to equipment to collect much more data on the operations of the equipment. Collecting and analyzing these data improves the maintenance process, increase productivity and reduces cost.

Media and Entertainment

  • Customer Insights – Media companies need to better understand market segments and consumer personal preferences and behavior to better match each brand to its segment and help increase sales.
  • Price analytics – Companies can use Hadoop to determine dynamic pricing for everything from game tickets, web bases games to music and videos.