Adam Price – Scaling iOS Development at Spotify
Want a behind the music look at mobile development at Spotify? In this talk, recorded at Spotify’s meetup last week, Adam price covers mobile development at spotify. Learn how they develop features in autonomous squads using static libraries within their iOS container application:
Podcast: Play in new window | Download
(Contributor article by 10gen, originally appeared on 10gen Blog)
According to new research from the UK’s Sector Skills Council for Business and Information Technology, the organization responsible for managing IT standards and qualifications, Big Data is a big deal in the UK, and MongoDB is one of the top Big Data skills in demand. This meshes withSiliconAngle Wikibon research I highlighted earlier, detailing Hadoop and MongoDB as the top-two Big Data technologies.
It also jibes with JasperSoft data that shows MongoDB as one of its top Big Data connectors:
MongoDB is a fantastic operational data store. As soon as one remembers that Big Data is a question of both storage and processing, it makes sense that the top operational data store would be MongoDB, given its flexibility and scalability. Foursquare is a great example of a customer using MongoDB in this way.
On the data processing side, a growing number of enterprises use MongoDB both to store and process log data, among other data analytics workloads. Some use MongoDB with its built-in MapReduce functionality, while others choose to use the Hadoop connector or MongoDB’s Aggregation Framework to avoid MapReduce.
Whatever the method or use case, the great thing about Big Data technologies like MongoDB and Hadoop is that they’re open source, so the barriers to download, learn, and adopt them are negligible. Given the huge demand for Big Data skills, both in the UK and globally, according to data from Dice and Indeed.com, it’s time to download MongoDB and get started on your next Big Data project.
John Jensen and Mike Sherman will be speaking about their problem domain over at Rich Relevance in this recording from the SF Data Mining Recommendation Engines Meetup at Pandora last week. At Rich Relevance, they provide content personalization as a service, mostly to retailers. Unlike Pandora, they don’t use intrinsic similarity metrics with in-depth knowledge about the domain they are recommending.
Podcast: Play in new window
| Download
Recommendation engines typically produce a list of recommendations in one of two ways – through collaborative or content-based filtering. Collaborative filtering approaches to build a model from a user’s past behavior (items previously purchased or selected and/or numerical ratings given to those items) as well as similar decisions made by other users, then use that model to predict items (or ratings for items) that the user may have an interest in. Content-based filtering approaches utilize a series of discrete characteristics of an item in order to recommend additional items with similar properties.
The following talk was recorded at the Recommendation Engines meetup at Pandora last night. Todd Holloway, Data Science Lead at Trulia, discusses the ins and outs of Trulia Suggest.
Podcast: Play in new window | Download
(Contributor article by 10gen, originally appeared on 10gen Blog.)
So much is written about Big Data that we tend to overlook a simple fact: most data isn’t big at all. As Bruno Aziza writes in Forbes, “it isn’t so” that “you have to be Big to be in the Big Data game,” echoing a similar sentiment from ReadWrite’s Brian Proffitt. Large enterprise adoption of Big Data technologies may steal the headlines, but it’s the “middle class” of enterprise data where the vast majority of data, and money, is.
There’s a lot of talk about zettabytes and petabytes of data, but as EMA Research highlights in a new study, “Big Data’s sweet spot starts at 110GB and the most common customer data situation is between 10 to 30TB.”
Small? Not exactly But Big? No, not really.
Continue reading »
Dr. Christian Posse was the last panelist at the recent Controlled Experimentation (A/B Testing) Meetup at Microsoft. In this talk, Christian shares some of the problems he’s seen in the social network field. Not a single piece of code, algorithm, feature, or user experience goes out without A/B Testing. He discusses their development of a system of hashing functions over at LinkedIn that allow them to run millions of A/B tests concurrently without interactions between them.
Podcast: Play in new window | Download
Original post with audio and slides is here.
Hey guys, you’re listening to g33ktalk. Today, we’ve got a talk by Ted Dunning from the Hadoop meet up in New York last night. Ted is going to talk to us about recent developments in Mahout. Stay tuned.
Ted Dunning: Okay, what I want to do is talk about news from Mahout, as if Mahout were a foreign land. Sometimes I think it is. I am chief application architect for MapR. Cool hat, huh? These hats are on offer. They go to employees— at least the black belt version goes to employee. And so, if you think you qualify for the black belt version, get in touch with us. We’re definitely hiring. You can get in touch with me a lot of ways. First initial, last name at maprtech. First initial, last name at apache dot org. Or, ted.dunning@gmail, ted_dunning @ Twitter. Any way you like. I try to answer everything, if anybody sends me anything, which sometimes means I work too late.
Continue reading »
g33ktalk is an innovative media company building an international network of startup oriented software engineers who love open-source technologies.
“Hacker” runs deep in our culture, and we’re looking for a startup-savvy content/growth hacker to help take our community to the next level. We’re looking for a special combination of tech blogger/product hustler who can work with our team to define the next steps in the user-facing vision of our platform and help create & execute our innovative distribution strategies.
Started by software engineer & serial entrepreneur Pete Soderling in 2012, we’ve currently launched in NYC and SF with plans to launch internationally this year. Via our own growth hacking techniques we’ve already built distribution to thousands of software engineers who trust g33ktalk to deliver high quality software engineering content.
You:
* have previously worked for, or founded, at least 1 startup (no posers)
* have experience with content marketing and can point to successful examples of of your work
* are wicked smart, write exceptionally well, have a dry sense of humor (you can’t blame us for wanting it all)
You, optionally:
* already write code
* have an interest in tech journalism
* have previous experience building a digital media product
You want:
* to be on the cutting edge of content marketing strategies, and part of a team building a platform that embodies them
* to help us take a stab at the crazy vision that a new media co doesn’t need to be funded by advertising
* to make the world a better place for software engineers
* the thrill of working on another early stage company
If you’re interested – email us at apply @ g33ktalk:
* send us at least one example of online content you’ve successfully produced & distributed
* tell us how you measure the success of your distribution
* include a list of the last 5 meetups you’ve attended