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I had the pleasure this past Wednesday of introducing Eric Pugh (@dep4b) to the Data Wranglers DC Meetup group. He spoke about using Solr and Zeppelin in data processing and; specifically, the ways big data can easily be processed and displayed as visualizations in Zeppelin. Also broached was Docker, an application Anant uses, and its role in setting up environments for data processing and analysis. Unfortunately, no actual blimps or zeppelins were seen during the talk, but the application of data analysis to events they usually fly over was presented on last month during a discussion about Spark, Kafka, and the English Premier League.
Instead of trying to completely rehash Eric’s presentation, please check out his material for yourself (available below). In short, he showed how multiple open-source tools can be used to process, import, manipulate, visualize, and share your information. More specifically, Spark is a fast data processing engine which you can use to prepare your data for presentation and analysis. Whereas, Zeppelin is a mature, enterprise-ready application; as shown by its recent graduation from Apache’s Incubator Program; and is a great tool to manipulate and visualize processed data.
Please don’t hesitate to reach out with any questions or if you are interested in participating or speaking at a future Data Wranglers DC event. Each event is recorded, livestreamed on the Data Community DC Facebook page and attended by 50 or more individuals interested in data wrangling, data processing, and possible outcomes from these efforts. After the monthly event, many members continue their discussions at a local restaurant or bar.
I hope to see you at an event in the near future!
The short answer is “To make it easy to package and ship code.”
Docker can be your assembly line for software production. If you’re building software with complex architecture, using software like Docker can significantly reduce the time for software development, testing, and deployment through the use of “containers”. For the client, this approach can significantly reduce software development costs, accelerate delivery cycles and launch times of ideas, and potentially decrease coding errors that hinder your services and hurt the bottom line. Docker is used by thousands of companies as part of their DevOps processes and its adoption is expected to continue to grow. Here are a few examples: Red Hat, Rackspace, Spotify, and more!
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