In this post, you’ll learn about a special data science giveaway and will get a sneak peak at the three talks I’m most excited about at DataEngConf NYC.
Two of my favorite Data Science Conferences are coming up in November (one in NYC and the other in SF), and you have a chance to win tickets to both of them! Here are the giveaway details:
- 1 conference ticket to DataEngConf NYC ($699)
- 1 conference ticket to MLconf San Francisco ($600)
- 1 AltWork Station($4900)
Enter Here Now:
Thanks to Our Sponsors:
This giveaway was made possible by the Learn Data Science Meetup community and by our amazing sponsors:
Hakka Labs, the creators of DataEngConf
Hakka Labs is an amazing community for data engineers and scientists comprised of thought leaders at influential tech companies like Google, Netflix, LinkedIn, Airbnb, Slack and many others. And as you know, DataEngConf is one of my favorite conferences (the content and the people attending are incredible!).
Created by my friend Courtney Burton, MLconf is a single day, single track event, devoted to the Machine Learning and Data Science community in major cities, agnostic of any tool, platform or company.
*Note: You can read more about MLconf’s and DataEngConf’s backstory in my Quora Answer: “Data Science Conferences - One List to Rule Them All”
DataEngConf - The Three Talks I’m Most Excited About
Here are the three talks at DataEngConf that I’m most excited about:
By Andy Pavlo - Carnegie Mellon University
Andy Pavlo, from Carnegie Mellon University, is one of the rising stars in databases. Even his job title is cool: Assistant Professor of Databaseology.
Andy argues that we need a DBMS that ‘manages’ itself, and doesn’t require human decision regarding the configuration or maintenance of underlying database mechanisms.
By Julien La Dem - Principal Architect at Dremio, Apache Parquet co-founder and PMC chair
Columnar storage has been one of the key innovations of the ‘big data’ era, and we’ll hear about the most up-to-date ways it’s currently being used in tools like Kudu, Ibis, Drill, Arrow and others.
By Guozhang Wang - Kafka Committer & Software Engineer, Confluent
Considering how ubiquitous Kafka has become in processing large amounts of data in the largest web platforms (starting at LinkedIn), I’m fascinated to see how Kafka Streams compare to Spark Streaming and which one will take the top spot in modern streaming architectures post Twitter’s Storm.
About Jared Polivka:
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