My five favorite talks from NYC* Big Data Tech Day
- Graph-based Recommendation Systems at eBay manages to give both a good overview of recommendation systems and an interesting Cassandra use case. Frankly, my experience is that most "Cassandra in Field X" talks manage to give a good Cassandra talk, or a good introduction to X, but not both. Thomas Pinckney's talk proved a happy exception. (During the Q&A, you can hear me ask why eBay doesn't use item-to-item collaborative filtering, which to my novice's perspective appears to be more popular currently. I'll leave you to the talk for Thomas's answer.)
- If you're at all interested in Storm, Kafka, or Elastic Search, I'd recommend Brian O'Neill's talk on integrating all three with Cassandra. I think Brian's just a little ahead of the curve here, and you're going to see a lot more from Storm and Kafka in particular this year.
- DataStax lost Jake Luciani as an employee to Blue Mountain Capital last year. I was sorry to see him go, but this does leave the world with one more Cassandra committer building applications in the trenches. I love seeing that because these people have the mentality not just of "how can I work around this problem I ran into with Cassandra," but also "how can I make Cassandra better to solve this problem for everyone?" Jake's talk with Carl Yesigian is a great example of applying this to time series financial data on the cutting edge of Cassandra 1.2. (And for a good overview of what's new in 1.2, I'll refer you to my own talk from NYC*.)
- Nathan Milford's talk on Cassandra administration was a good change of pace from the talks focused on architects and developers. Even if you aren't at all interested in sysadmin procedures, though, you need to watch this for Nathan's unique introduction. I've never seen anything like it at a tech conference.
- Last but not least, you should definitely check out Michaël Figuière's talk on DataStax's new CQL drivers for Java and C#. CQL is a huge step forward and having drivers that speak it natively are going to make a night-and-day difference in Cassandra development productivity. Check it out.
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