The 10 worst big data practices

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Yes, you can haz big data. However, you can haz it the right way or the wrong way. Here are the top 10 worst practices to avoid.

1. Choosing MongoDB as your big data platform. Why am I picking on MongoDB? I’m not, but for whatever reason, the NoSQL database most abused at this point is MongoDB. While MongoDB has an aggregation framework that tastes like MapReduce and even a (very poorly documented) Hadoop connector, its sweet spot is as an operational database, not an analytical system.

When your sentence begins, “We will use Mongo to analyze …,” stop right there and think about what you’re doing. Sometimes you really mean “collect for later analysis,” which might be OK, depending on what you’re doing. However, if you really mean you’re going to use MongoDB as some kind of sick data-warehousing technology, your project may be doomed at the start.

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iOS developers poised to win big in Apple-IBM deal

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Mobile developers with knowledge of Objective-C and Apple’s fledgling Swift language could be the big winners in Apple’s newly announced partnership with IBM.

That alliance has IBM firmly endorsing the iPad, with Big Blue reselling Apple’s popular tablet device preconfigured with enterprise apps for vertical industries. More iPads will end up at large IBM shops, opening up new markets for iOS application builders.

Some — but not all — iOS developers could have a major opportunity to earn lots of income in the enterprise space, said iOS application developer Christopher Allen, CTO of software developer ReOrientmedia.com. “Working at an enterprise level often requires ‘full stack’ skills, from UX to client engineering and on through to a scalable back end, which is the kind of experience the more indie app developers don’t have,” he noted. “Those teams that have this broader experience will do well.”

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Review: Cloud Foundry brings power and polish to PaaS

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Cloud Foundry was created by VMware to streamline deployment for application developers, application operators, and cloud operators. Then in April 2011, Cloud Foundry was announced as open source under the Apache 2.0 license, with the pitch to developers that they could code in the language and Web framework of their choice without worrying about the IT environment.

In February 2014, VMware spin-off Pivotal announced the formation of the Cloud Foundry Foundation, with Pivotal, EMC, IBM, Rackspace, and VMware as Platinum sponsors. The foundation has since expanded to 33 members and 42 contributing companies. One differentiator for Cloud Foundry is support for Pivotal HD Hadoop MapReduce, HAWQ SQL for Hadoop, and GemFire XD analytics. Another is the availability of the Pivotal Mobile Services Suite, thanks to last year’s acquisition of Xtreme Labs. Pivotal’s big data services and mobile services are both now integrated with Pivotal CF, the company’s enterprise version of Cloud Foundry.

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Google thinks global Internet security with Project Zero

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Google is increasing its efforts in Internet security and is looking to hire security researchers for its newly formed Project Zero team.

In a post in Google’s Online Security Blog, Google researcher Chris Evans said that people should be able to use the Web without fear that a criminal or state-sponsored actor is exploiting software bugs to infect a computer, steal secrets, or monitor communications, but sophisticated zero-day day attacks, targeting human rights activists, for example, or for industrial espionage, are threats. Google believes more can be done to tackle the problem.

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Python bumps off Java as top learning language

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Python has surpassed Java as the top language used to introduce U.S. students to programming and computer science, according to a recent survey posted by the Association for Computing Machinery (ACM).

Eight of the top 10 computer science departments now use Python to teach coding, as well as 27 of the top 39 schools, indicating that it is the most popular language for teaching introductory computer science courses, according to Philip Guo, a computer science researcher who compiled the survey for ACM.

The three largest, most popular online class providers — Coursera, edX and Udacity — also offer introductory programming courses in Python, Guo found.

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DataStax Enterprise 4.5 turbocharges speed and security

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Datastax Enterprise is the commercial distribution of Apache Cassandra, a column-family NoSQL database developed by Facebook and probably best known for powering Netflix. The new 4.5 release of DataStax Enterprise, announced June 30, advances DataStax’s case that NoSQL is ready for enterprise applications. It features Apache Spark integration for fast in-memory analytics, Hortonworks and Cloudera integration for easy access to Hadoop data, and new diagnostic and security tools.

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Oracle hopes to entice mobile developers with new framework

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Oracle is hoping it can attract more developers with MAF (Mobile Application Framework), which aims to simplify the development of cross-platform enterprise apps for smartphones and tablets.

As a result of the growing number of smartphones and tablets employees have, software vendors are increasingly focusing on how to make enterprise applications more mobile friendly. On Monday, Oracle announced updates to its Mobile Suite, which aims to do just that.

The heart of the new release is MAF, which builds on the cross-platform development tools Oracle already offers. The framework lets developers choose between the JDeveloper IDE (integrated development environment) or Enterprise Pack for Eclipse. Developers can also choose among a number of development languages, including Java, JavaScript and HTML5, when developing native Android and iOS apps, according to Oracle.

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In praise of Java template engines

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One enterprise tech trend to rule them all

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Recently I was asked what I thought was the most important trend in IT. And it wasn’t hard to answer: The shift from proprietary, scale-up systems to commodity, open source, scale-out systems.

NoSQL databases provide a good example of scaling out versus up. To beef up Oracle or any other conventional, proprietary RDBMS, you need to scale up the database server with more cores, more caching, more flash, and so on. At a certain point, you’ll need another server, which means you’ll be saddled with sharding the database and maintaining it in that state (yes, you could use Oracle RAC, but that’s another story).

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Docker containers with Gradle in 4 steps

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Do you need to create a Docker image from your Java web app? Are you using Gradle? If so, then you are only four steps away from Docker Nirvana.

For this example, I’m going to use a simple Spring Boot application. You can find all the source code in my Github repository dubbed galoshe.

If you haven’t had a chance to see Spring Boot in action, then you’re in for a treat, especially if the words simple and Java web app in the same sentence make you flinch. That was certainly my long standing reaction until I took a serious look at Boot.

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Do Twitter analysis the easy way with MongoDB

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With all the World Cup excitement, I found myself wondering what the Twitter-scape looked like. Who is tweeting? What are they tweeting about? Where are they? What language are they tweeting in?

Obviously, such questions can apply to any tweet-worthy event. Along with the idly curious like me, various types of businesses from tech startups to local restaurants might want to know: What’s my most vocal demographic? What time of day are people tweeting about my service most often? How do people feel about the new website?

Collecting all this data and analyzing it might seem like a big investment, but with the right tools it becomes trivially easy. In this article, I show you how to analyze tweet data using MongoDB as both the data store and the analytics engine. MongoDB has powerful analytics tools and straightforward pluggability into Hadoop for when you have a question that needs a more generic tool. I’m using tweets about the World Cup to demonstrate, but the concepts are generic and can be easily applied to your own data set.

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