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Rahul Singh, CEO of Anant, had the opportunity to co-organize and MC the May Meetup of Data Wranglers DC where the speakers, John Clune and Timothy Hathaway, covered two topics related to open government and public data for data processing and visualization. We had a great turnout at the event and had the chance to do some networking after.
Our next two meetups will focus on Search & Knowledge Management (June Meetup) and Machine Learning for Data Processing (July Meetup), check out the Meetup page for more details when they become available.
Big thank you to John Clune and Timothy Hathaway for taking the time to present to the group if you have any interest in speaking please don’t hesitate to reach out to Rahul at firstname.lastname@example.org.
Below you can find a recording of both presentations.
As technology has continued to mature in the last two decades there have been many challenges overcome, obstacles faced, and solutions crafted. A recurring theme, in the area of obstacles (more specifically, self-imposed obstacles), has been the propensity for software companies to more often than not 1) turn to developing applications from the ground up for a particular problem or 2) take existing pieces of software that are perfectly fine for their specific use case and then tailor them to a different (but sometimes slightly similar) use case.
Software Algebra is essentially a best practice in software development to make sure that we are using 1) the tools best suited to a particular problem 2) while also dodging the trap of re-inventing the wheel by starting from scratch or trying to fit a tool into solving a problem it was never intended to address.
There are multiple cases in which this best practice is entirely ignored, most commonly so by inexperienced software architects who have the “my hammer can solve all problems” mindset. Often times, one of the best ways to avoid falling into this trap is to relentlessly focus on getting a Minimal Viable Product (MVP) out of the door in a time-boxed span of time and iterating multiple times on that MVP to steadily bring it up to support all use cases.
We recently spoke about this topic at the WebTech Conference in Washington, DC and will be doing so again on Tuesday, April 11th at 6PM at the University of Maryland Baltimore County, you can find additional details as well as register for the event here.
Rahul Singh will be presenting on Thursday, March 30th at WebTech on the topic of Software Algebra. He’ll be speaking about the ways online software (SaaS) and open source applications can work in tandem with web and mobile applications to deliver powerful business results.
From this presentation, you will learn how to plan and build web apps that support business process using existing software. This approach takes a very practical approach to taking inventory of business teams, processes, information, and systems and creating future-proof web systems without reinventing the wheel.
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!
A: 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!
One of Docker’s great attributes is its ‘malleability.’ You can rapidly build things and tear them down if needed, enabling you to nimbly adapt when an urgent application deployment arises. Docker’s greatest utility is in situations where a client or project needs to quickly stand up a developing and testing environment, an application, and all the associated dependencies. We plan to show how we are using Docker internally and externally to service both our clients’ and our needs.
To a technologist, the beneficial aspects of Docker are clear; however, there are other benefits that accrue to the end user as well. First, the end user more than likely will not need to modify their hardware and software setup to accommodate Docker assembled applications. Applications will not force the user to restart the whole application or worry about ‘fluff’ filling their servers. Finally, the isolation feature inherent with Docker containers walls off the application while also reducing the draw on computing power providing some additional security advantages and better overall performance of computing platforms.
The workshop on 12/17 will focus on the technical side of using Docker. We will present Docker basics for both Linux and Windows, as well as doing a review of Docker Compose and other Docker tools. While we want everyone to know and share about how to use these features, we hope you can explain why Docker is being adopted and how end users also benefit.