Co-Authors: Sumedh Sakdeo, Lei Sun, Sushant Raikar, Stanislav Pak, and Abhishek Nath Introduction At LinkedIn, we build and operate an open source data lakehouse deployment to power Analytics and Machine Learning workloads. Leveraging data to drive decisions allows us to serve our members with better job insights, and connect the world’s professionals with each...
Data Articles
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- Topics:
- infrastructure,
- Big Data,
- Data
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Imagine a tool that can store and connect all the information you need to make decisions and solve problems. Most people would say it’s nice to think about, but not yet possible. The good news is this tool already exists - and it’s called a graph database. At LinkedIn, technologies like graph databases are essential to powering today's platform, while being...
- Topics:
- scale,
- infrastructure,
- knowledge graph,
- Data
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With the widespread adoption of Rest.li since its inception in 2013, LinkedIn has built thousands of microservices to enable the exchange of data with our engineers and our external partners. Though this microservice architecture has worked out really well for our API engineers, when our clients need to fetch data they find themselves talking to several of these...
- Topics:
- rest.li,
- Data,
- Open Source
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For our engineering teams, artificial intelligence (AI) is like oxygen - it powers every product we build and every experience we...
- Topics:
- artificial intelligence,
- AI,
- Data
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Based in Silicon Valley, Priya serves on LinkedIn Engineering’s Technical Program Management (TPM) team, supporting our large-scale,...
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Co-authors - Blake Lawit and Ya Xu Editors Note: This post originally appeared on LinkedIn's Official Blog. LinkedIn was founded with...
- Topics:
- artificial intelligence,
- machine learning,
- AI,
- Policy,
- Data