Hadoop Progress Report: 3 Emerging Use Cases

Source: Hadoop Progress Report: 3 Emerging Use Cases

Big Data & Humans

Source: Big Data & Humans

Baidu claims deep learning breakthrough with Deep Speech

Gigaom

Chinese search engine giant Baidu says it has developed a speech recognition system, called Deep Speech, the likes of which has never been seen, especially in noisy environments. In restaurant settings and other loud places where other commercial speech recognition systems fail, the deep learning model proved accurate nearly 81 percent of the time.

That might not sound too great, but consider the alternative: commercial speech-recognition APIs against which Deep Speech was tested, including those for [company]Microsoft[/company] Bing, [company]Google[/company] and Wit.AI, topped out at nearly 65 percent accuracy in noisy environments. Those results probably underestimate the difference in accuracy, said [company]Baidu[/company] Chief Scientist Andrew Ng, who worked on Deep Speech along with colleagues at the company’s artificial intelligence lab in Palo Alto, California, because his team could only compare accuracy where the other systems all returned results rather than empty strings.

Ng said that while the research is still just research…

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A TRIP DOWN MEMORY LANE: Cloud databases 101: Who builds ’em and what they do

Gigaom

Remember when there were just two or three cloud computing platforms to choose from, and just about as many cloud databases? Well, as clouds have proliferated, so have the database services built on top of them. In fact, it’s getting hard to keep up with what’s actually available.

Here’s a primer highlighting the available services (note, we’re talking managed database services, not database instances that users still need to manage and administer) and where they’re running. It’s intended to be thorough, but that can be easier said than done, so please note any omissions in the comments.

SQL services

• Amazon Relational Database Service:One of the first cloud database services, Amazon Web Services’ RDS is now one of the most complete, too. Like most AWS (s amzn) services, it’s tied into the AWS management interface and is compatible with a large majority of AWS’s countless other cloud computing services…

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Hortonworks did $12.7M in Q4, on its path to a billion, CEO says

Gigaom

Hadoop vendor Hortonworks announced its first quarterly earnings as a publicly held company Tuesday, claiming $12.7 million in fourth-quarter revenue and $46 million in revenue during fiscal year 2014. The numbers represent 55 percent quarter-over-quarter and 91 percent year-over-year increases, respectively. The company had a net loss of $90.6 million in the fourth quarter and $177.3 million for the year.

However, [company]Hortonworks[/company] contends that revenue is not the most important number in assessing its business. Rather, as CEO Rob Bearden explained around the time the company filed its S-1 pre-IPO statement in November, Hortonworks’ thinks its total billings are a more accurate representation of its health. That’s because the company relies fairly heavily on professional services, meaning the company often doesn’t get paid until a job is done.

The company’s billings in the fourth quarter totaled $31.9 million, a 148 percent year-over-year increase. Its fiscal year billings were $87.1 million, a 134 percent…

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What is Azure Machine Learning and why is it important: 4 Examples

KevinMcCauley.com

Azure Machine learning — getting a system to teach itself from lots of data rather than simply following preset rules — actually powers the Microsoft software you use everyday.

Examples

1. Machine learning enables Clutter in Office 365 to determine with uncanny accuracy which email
2. Makes it easier to touch the right menu on a Windows tablet with your finger
3. Helps OneNote figure out your handwriting.
4. If you’re selling handbags, dresses, shoes, or other fashion items on eBay, you might see much better sales overseas because automatic translations of listings are more accurate — and available in all 45 languages Azure ML supports.

InfoWorld

Full Story: Yesterday’s announcement of Azure Machine Learning offers the latest sign of Microsoft’s deep machine learning expertise — now available to developers everywhere.

Microsoft Azure ML Site: http://azure.microsoft.com/en-us/services/machine-learning/ 

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10 Big Data Certifications That Will Pay Dividends [ Source: Ingram Micro – Big Data Blog ]

Despite the buzz, big data is still in its infancy which means that there are few true big data experts. Of course, that doesn’t stop newcomers from claiming expertise. The only way you can demonstrate to your customers and prospects that you have a mastery of big data is with big data certifications.

The biggest big data skills gap is in data science. According to a CompTIA survey of IT executives at 500 U.S. businesses, 50 percent of firms say they are ahead of the game in leveraging data, but 71 percent feel that their staff skills in data management and analysis are lagging. And the McKinsey Global Institute predicts that the shortfall in data science skills is going to continue. By 2018 they predict a shortage of 1.7 million workers with the necessary big data skills. That includes 140,000 to 190,000 experts with deep technical and analytical skills, and 1.5 million managers with the analytical savvy to work with big data results.

So if you want to acquire big data credentials, the best place to focus is on certifications that demonstrate your prowess in big data framework design and analytics. Many of these big data certifications are offered by vendors, but more big data credential programs are emerging from universities as well. Here is a short list of 10 of the big data certifications that discerning organizations are starting to look for:

1. Certified Analytics Professional (CAP)
2. HP Vertica Certification
3. EMC Data Scientist Associate (EMCDSA)
4. Cloudera Certified Professional: Data Scientist (CCP:DS)
5. Cloudera Certified Developer for Apache Hadoop (CCDH)
6. Cloudera Certified Administrator for Apache Hadoop (CCAH)
7. Cloudera Certified Specialist in Apache HBase (CCSHB)
8. Revolution R Enterprise Professional
9. Certificate in Engineering Excellence in Big Data Analytics and Optimization (CPEE)
10. Graduate Certificate: Mining Massive Data Sets

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That IPO? Cloudera bides its time [ Source: Fortune.com ]

The high-profile Hadoop software company signed 250 new big-business accounts in 2014, topping $100 million in annual revenue. But CEO Tom Reilly is in no rush to go public.

Tomorrow, big data management company Hortonworks will report its first financial results since going public last December. Privately held Cloudera—one of its fiercest rivals in Hadoop software and backed with more than $1.2 billion from the likes of Intel—isn’t subject to the same scrutiny. But like any startup contemplating an initial public offering, it occasionally discloses revenue and customer milestones to pique our interest.

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For now, Spark looks like the future of big data

Gigaom

Titles can be misleading. For example, the O’Reilly Strata + Hadoop World conference took place in San Jose, California, this week but Hadoop wasn’t the star of the show. Based on the news I saw coming out of the event, it’s another Apache project — Spark — that has people excited.

There was, of course, some big Hadoop news this week. Pivotal announced it’s open sourcing its big data technology and essentially building its Hadoop business on top of the [company]Hortonworks[/company] platform. Cloudera announced it earned $100 million in 2014. Lost in the grandstanding was MapR, which announced something potentially compelling in the form of cross-data-center replication for its MapR-DB technology.

But pretty much everywhere else you looked, it was technology companies lining up to support Spark: Databricks (naturally), Intel, Altiscale, MemSQL, Qubole and ZoomData among them.

Spark isn’t inherently competitive with Hadoop — in fact, it…

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