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| Alice Zheng describes an epiphany she had while trying to grok linear algebra: how becoming more familiar with mathematics can cross pollinate ideas between mathematics and software engineering. (Alice will also be speaking at Large-scale Machine Learning Day at Strata + Hadoop World.) |
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| Do any of these sound like you? |
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| The ELK Stack (Elasticsearch, Logstash, Kibana) is hot, hot, hot. If you want to dive deep into the ELK Stack, there will be a tutorial at Strata + Hadoop World San Jose. (If you’re interested, sign up quickly, tutorials have limited seating.) |
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In February, Big Data's biggest event comes to the Bay Area. Get a sneak peek with this free online conference on Friday Feb 4, featuring many of Strata's hottest topics and most sought-after speakers, including: Paco Nathan, June Andrews, Ross Fubini, Danyel Fisher, Joe Hellerstein, Dave Holz, and Alistair Croll.
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| In this podcast, DJ Patil weighs in on a wide range of topics in data science and big data. |
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 Today, Adam Marcus will discuss "how I learned to stop worrying and love the crowd," that will highlight how GoDaddy builds human-machine hybrids and benefits form active learning workflows" in a free webcast. (If you miss it, you can still watch the replay.)
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| Ian Bogost argues: "Our supposedly algorithmic culture is not a material phenomenon so much as a devotional one, a supplication made to the computers we have allowed to replace gods in our minds, even as we simultaneously claim that science has made us impervious to religion." |
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| Mapping beyond data mining: a TED talk on happy maps. |
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| The deadline for the Strata + Hadoop World San Jose Startup Showcase CFP is this Friday, Jan 23. If you've got a startup that deserves a little attention from the movers and shakers (and investors) in the data world, this is your chance. |
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You can now take the Spark Developer Certiification exam online.
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| Computer scientists at the University of Houston have devised a way to make conventional memory discs 99.999% reliable over a 4-year lifespan. |
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 Get the first two chapters of the book, Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems, compliments of Pentaho. It will help you navigate the diverse and fast-changing landscape of technologies for processing and storing data (NoSQL, big data, MapReduce, etc). It looks at examples of successful data systems and discusses their key algorithms, basic principles, and the trade-offs they have to make in order to meet scalability, performance, and reliability requirements.
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