Big Data Application Examples in Different Industries

When the tremendous amount of technological advancements that have been introduced and changed the world in the years passed, the amount of information being created and stored on a global level has also grown enormously. The large volume of data generated by different sources from business transactions, social media, to machines and equipment embedded with sensors is collectively known as “Big Data”. Although the term is considerably new for most of us, it has already started changing the overall landscape of different industries. Big data analytics solutions help you to understand your brand, market perception and design perfect strategy for analyzing various segments related to your product and industry. It helps to get insights into a huge amount of data. Let’s see application examples of Big Data in different industries here:

Big Data Application Examples in Different Industries


  • Merchandising and market basket analysis
  • Campaign management and customer loyalty programs
  • Supply-chain management and analytics
  • Event- and behavior-based targeting
  • Market and consumer segmentation

Health & Life Sciences

  • Clinical trials data analysis
  • Disease pattern analysis
  • Campaign and sales program optimization
  • Patient care quality and program analysis
  • Medical device and pharmacy supply-chain management
  • Drug discovery and development analysis

Finances & Frauds Services

  • Compliance and regulatory reporting
  • Risk analysis and management
  • Fraud detection and security analytics
  • Credit risk, scoring, and analysis
  • High-speed arbitrage trading
  • Trade surveillance
  • Abnormal trading pattern analysis


  • Revenue assurance and price optimization
  • Customer churn prevention
  • Campaign management and customer loyalty
  • Call detail record (CDR) analysis
  • Network performance and optimization
  • Mobile user location analysis

Web and Digital media

  • Large-scale clickstream analytics
  • Ad targeting, analysis, forecasting, and optimization
  • Abuse and click-fraud prevention
  • Social graph analysis and profile segmentation
  • Campaign management and loyalty programs

E-commerce & customer service

  • Cross-channel analytics
  • Event analytics
  • Recommendation engines using predictive analytics
  • Right offer at the right time
  • Next best offer or next best action

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