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:
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.
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.
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.
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.
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