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Dean Wampler, TweetBig Dataist, O'Reilly Author
Biography: Dean Wampler
Dean Wampler specializes in the application of Functional Programming principles to “Big Data” applications, using Hadoop and alternative technologies. Dean is a contributor to several open-source projects and the founder of the Chicago-Area Scala Enthusiasts. He is the author of Functional Programming for Java Developers, the co-author of Programming Scala, and the co-author of Programming Hive, all from O’Reilly. He pontificates on twitter, @deanwampler, and at polyglotprogramming.com. His consulting company is Concurrent Thought.
Twitter: @deanwampler
Presentation: TweetFrom Big Data to Big Information
The Big Data landscape is at a crossroads. Currently dominated by Hadoop and NoSQL databases, alternatives to Hadoop and next-generation datastores are emerging.
Many organizations are adopting Big Data technologies, primarily Hadoop and NoSQL databases, because they don’t want to be left behind. They face a daunting task of understanding the strengths and weaknesses of these evolving tools and how they actual meet specific business objectives… or don’t. Ultimately, the promises of Big Data include cost savings, greater scalability, and new ways of extracting useful information from data sets that were previously unmanageable.
This talk describes some lessons I’ve learned while consulting on Big Data projects. I’ll comment on the strengths and weaknesses of several representative tools and offer guidance for evaluating others. I’ll discuss how to craft integrated solutions that are focused on meeting particular goals. In other words, how to focus on extracting useful information, rather than just managing data.
Many organizations are adopting Big Data technologies, primarily Hadoop and NoSQL databases, because they don’t want to be left behind. They face a daunting task of understanding the strengths and weaknesses of these evolving tools and how they actual meet specific business objectives… or don’t. Ultimately, the promises of Big Data include cost savings, greater scalability, and new ways of extracting useful information from data sets that were previously unmanageable.
This talk describes some lessons I’ve learned while consulting on Big Data projects. I’ll comment on the strengths and weaknesses of several representative tools and offer guidance for evaluating others. I’ll discuss how to craft integrated solutions that are focused on meeting particular goals. In other words, how to focus on extracting useful information, rather than just managing data.