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Fault Tolerant Data: Surviving the Zombie Apocalypse

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No logo availableConfreaks, LLC
 Rosenthal, Casey

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Fault Tolerant Data: Surviving the Zombie Apocalypse
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50
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CC Attribution - ShareAlike 3.0 Unported:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor and the work or content is shared also in adapted form only under the conditions of this
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Production PlaceMiami Beach, Florida

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Acute Zombielepsy has broken out, and the CDC has turned to you to store the first one million records of victims in the U.S. including the subject’s name, DNA sample, geo, etc. You must store this crucial data in a resilient manner in case one or more data centers are compromised by the outbreak. The CDC also needs to query the data in several ways; for example, they want to see the outbreak on a map to visualize geographic clusters. Naturally, you turn a fault-tolerant NoSQL database to store this data. But since you come from a relational background, you find it difficult at first to model the data properly for the types of queries that the CDC wants to run. Learn about advanced data modeling on a key-value database in Ruby -- distributed indexes, convergent data types, geohashes, and more -- on a truly fault tolerant database infrastructure. Keep calm; the fate of the human race depends on you.
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