“Systems are giving up correctness for latency, and I’m arguing that stream processing systems have to be designed to allow the user to pick the tradeoffs that the application needs."

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“We still need to see in the long run how much of community and industry adoption is there. Because at the end of the day, these are the single two most important things which define and determine the success of any platform.”

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“We want people to be able to pick up whatever tool it is and really push themselves to get something done with it in a short amount of time, because that’s ultimately what they need to do as a data engineer in the industry.”

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“It’s a great time to be an engineer.”

Information retrieval and search engineering are becoming more intertwined with machine learning and natural language processing, leading to a wealth of work to be done in the field.

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“Everybody that sees SQL thinks its ugly and dirty and they want to try and rewrite it to be better. There’s a bazillion attempts to do this - I’ve tried it several times myself. But somehow, everybody always comes back to SQL.”

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“My bet is that there is going to be a big shift towards streaming technologies in the future.”

Apache Flink is an open-source framework for distributed stream and batch data processing.

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“There’s not enough data scientists out there, and every company wants them to do everything. So, you really have to focus on ‘How can I be most impactful with the limited time and resources I have?’ ”

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“If you have an architecture where you’re trying to periodically trying to dump from one system to the other and synchronize, you can simplify your life quite a bit by just putting your data in this storage system called Kudu.”

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“There are a lot more people who have the problem that Hadoop solves than there are people using Hadoop.”

Pachyderm is a containerized data analytics platform that seeks to replace Hadoop.

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"A lot of data science teams - if you ask them what their ten most important questions are... a lot of people can't even come up with those."

Many companies find themselves drowning in data. The quantity of data matters far less than the right questions in the pursuit of actionable insights.

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