Hadoop: What it is, how it works, and what it can do. Hadoop gets a lot of buzz these days in database and content management circles, but many people in the industry still don’t really know what it is and or how it can be best applied. Cloudera CEO and Strata speaker Mike Olson, whose company offers an enterprise distribution of Hadoop and contributes to the project, discusses Hadoop’s background and its applications in the following interview. Where did Hadoop come from? Mike Olson: The underlying technology was invented by Google back in their earlier days so they could usefully index all the rich textural and structural information they were collecting, and then present meaningful and actionable results to users.
There was nothing on the market that would let them do that, so they built their own platform. Google’s innovations were incorporated into Nutch, an open source project, and Hadoop was later spun-off from that. What problems can Hadoop solve? Hadoop applies to a bunch of markets. How is Hadoop architected? Related: Data Science and Big Data Analytics Training. Q&A: What's needed to get a big data job? News October 24, 2012 12:37 PM ET Computerworld - The torrents of data produced by social networks, sensors, supply chains and every imaginable device are creating new jobs. Gartner estimated this week that big data will create 1.9 million new jobs in the U.S. through 2015. Michael Rappa saw this emerging trend and in 2007 became the founding director of the Institute for Advanced Analytics at North Carolina State University, which created a Master of Science in Analytics program, the first academic program devoted to data analytics.
Rappa continues as the Insitute's director. Universities around the U.S. are now establishing similar advanced degree programs. In an interview this week, Rappa, who previously taught at MIT, explains what constitutes a big data job and the types of training people will need to get them. What constitute a big data job? It's not uncommon for employers to come to the Institute looking for big data talent without a written job description. Big data, big jobs? By Tam Harbert September 20, 2012 06:00 AM ET Big data also demands a scientific temperament, according to Wills.
"When we talk about data science, it's really an experiment-driven process," he explains. "You're usually trying lots of different things, and you have to be OK with failure in a pretty big way. " Wills speaks of a "certain kind of relentlessness you need in the personality of someone who does this kind of work. " They also have to be intellectually flexible enough to quickly change their assumptions and approach to a problem, says Brian Hopkins, a principal analyst at Forrester Research.
That tends to be a different operating model than most IT people are used to, he says. But hiring managers, once they find the right type of person, are usually willing to retrain that person to fill a big data role. As for employees, certain IT folks would love to flex a more creative muscle in their jobs, and they may be able to segue into a big data career. Taming Big Data | A Big Data Infographic. Grad schools add big-data degrees. News Analysis October 8, 2012 06:00 AM ET Computerworld - Colleges and universities are moving swiftly to create advanced degree programs to help meet what's expected to be rapidly rising demand among employers for specialists who can manage and analyze big data. The schools are likely aware of a McKinsey report warning of a mega-shortage of analytical experts that could leave as many as 190,000 positions unfilled by 2018.
They're also responding to appeals from big employers like IBM and SAS Institute that have been lobbying college administrators to set up such programs. Schools have offered analytics training for years, but the emerging advanced degree programs add instruction in the use of analytic and business intelligence tools to produce useful information from petabytes of data collected from social media sites, sensors, transaction records, mobile applications and other sources. This version of this story was originally published in Computerworld's print edition. Big data buzzwords: A to Z - Photo Galleries. What is Big Data? | Big Data | Research, Articles, Media.
Big Data Research and Analysis from The Wikibon Project The best of Wikibon's Big Data research and analysis. Follow Wikibon Big Data Analyst Jeff Kelly on Twitter and LinkedIn. For a list of Wikibon clients, click here. Also see Wikibon's research on disruptions to infrastructure on the Software-led Infrastructure page. Big Data Market Forecasts Big Data Vendor Revenue and Market Forecast 2013-2017 NEW REPORT FEBRUARY 10, 2014The Big Data market is on the verge of a rapid growth spurt that will see it over the $50 billion mark worldwide within the next five years.
Hadoop-NoSQL Software and Services Market Forecast 2012-2017 The market for Hadoop/NoSQL software and services topped $540 million in 2012 as measured by vendor revenue. Big Data Database Revenue and Market Forecast 2012-2017 The research behind this article drills down into the database components, Big Data SQL database revenue, and Big Data NoSQL database revenue, highlighted in Figure 1. Big Data Manifestos and Definitions. Big data: The next frontier for innovation, competition, and productivity | McKinsey Global Institute | Technology & Innovation.
The amount of data in our world has been exploding, and analyzing large data sets—so-called big data—will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus, according to research by MGI and McKinsey's Business Technology Office. Leaders in every sector will have to grapple with the implications of big data, not just a few data-oriented managers. The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data for the foreseeable future. MGI studied big data in five domains—healthcare in the United States, the public sector in Europe, retail in the United States, and manufacturing and personal-location data globally.
Big data can generate value in each. 1. 2. Podcast Distilling value and driving productivity from mountains of data 3. 4. 5. 6. 7.