Andrea Burbank - Data Communicator at <a href="https://www.pinterest.com/">Pinterest</a>
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ABSTRACT
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Four years at Pinterest show how building a data-driven culture both arises from and contributes to software engineering practices. The talk will touch on building data infrastructure.
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Data Science

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   <li>Who is coming to our services?</li>
   <li><a href="https://kafka.apache.org/">Kafka logging</a></li>
   <li><a href="https://en.wikipedia.org/wiki/Daily_active_users">Daily active users</a></li>
   <li>Weekly Active Users / Monthly Active Users / Yearly Active Users</li>
   <li>Instead of holding all the data in a database for a whole year, create derived tables: e.g. DAU that holds one line for each user who visited the site that day. Also create WAU and MAU.</li>
   <li>Spam filtering</li>
   <li>Prefetch of pages will mess with your data.</li>
   <li><q>Data chaos: table proliferation</q></li>
   <li>Data Clarity: <a href="https://thrift.apache.org/">thrift</a></li>
   <li><q>Avoid Data chaos: well-structured data, well understood.</q></li>
   <li><q>Spectum of certainty: correlation vs causation</li>
   <li>A/B testing</li>
   <li><q>Doing the right thing should be easy. Doing the wrong thing should be hard.</q></li>
   <li><q>Counting is hard</q></li>
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