Co-authors: Steven Chuang, Qinyu Yue, Aravind Rao, and Srihari Duddukuru Introduction Having recently transitioned LinkedIn’s analytics stack (including 1400+ datasets, 900+ data flows, and 2100+ users) to one based on open source big data technologies, we wanted to give an overview of the journey in a blog post. This move freed us from the limits imposed by...
Analytics Articles
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Co-authors: Siddharth Teotia and Tim Santos Introduction LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph...
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Co-authors: Krishnaram Kenthapadi, Thanh Tran, Mark Dietz, and Ian Koeppe Preserving privacy of users is a key requirement of web-scale data mining applications and systems such as web search, recommender systems, crowdsourced platforms, and analytics applications. With the growing appreciation of the impact of data breaches and comprehensive data regulations,...
- Topics:
- trust engineering,
- Analytics,
- research,
- Data
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I’m sure everyone who has been following tech industry news knows about “big data” and “AI.” Although there is no industry-consistent...
- Topics:
- Craftsmanship,
- data science,
- machine learning,
- Analytics,
- Data
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Qingbo Hu is a Senior Business Analytics Associate in LinkedIn’s Analytics Data Mining team. His team provides end-to-end data mining...
- Topics:
- engineering culture,
- data science,
- Analytics,
- Data Mining
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What is the shape of your big data? While we do love to talk about the size of our big data—terabytes, petabytes, and beyond—perhaps...
- Topics:
- Big Data,
- machine learning,
- data science,
- Analytics