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How is LinkedIn using bigdata?

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LinkedIn leverages big data in various ways to enhance its platform and services. Here are a few examples: 1. **Personalized Recommendations**: LinkedIn analyzes vast amounts of user data to provide personalized job recommendations, content suggestions, and networking opportunities tailored to each...
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LinkedIn leverages big data in various ways to enhance its platform and services. Here are a few examples: 1. **Personalized Recommendations**: LinkedIn analyzes vast amounts of user data to provide personalized job recommendations, content suggestions, and networking opportunities tailored to each user's interests, skills, and career goals. 2. **Talent Acquisition**: Big data analytics helps LinkedIn's recruiting tools to identify and match suitable candidates with job openings by analyzing factors such as skills, experience, location, and connections. 3. **Content Curation**: LinkedIn uses big data to curate and prioritize content in users' feeds based on their interests, interactions, and network connections, ensuring they see the most relevant and engaging posts. 4. **Advertising Targeting**: LinkedIn's advertising platform utilizes big data to target specific demographics, industries, job titles, and interests, enabling advertisers to reach their desired audience more effectively. 5. **Market Insights**: LinkedIn aggregates and analyzes user-generated data to provide insights into industry trends, job market dynamics, skill demand, and workforce demographics, which can be valuable for businesses, recruiters, and policymakers. Overall, LinkedIn's use of big data helps enhance user experience, drive engagement, facilitate networking, and provide valuable insights for professionals and businesses. read less
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LinkedIn's data infrastructure uses Hadoop for batch processing. LinkedIn pre-computes the data for “People You May Know” product by recording close to 120 billion relationships per day in a Hadoop MapReduce pipeline, that runs 82 Hadoop jobs which require 16TB of intermediate data
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