Monthly Archive: August 2015
**This post originally published on InsideBigData**
Everybody wants a piece of the big data pie – particularly Hadoop. Startups are popping up left and right in attempt to be a part of the Hadoop action and industry watchers are fueling the buzz — and for good reason.
Hadoop has emerged as the leading software framework for the storage and analysis of big data. Early adopters such as Facebook, Twitter and Yahoo! have successfully built custom analytics using Hadoop to tackle big data analytic challenges. Given this initial success, Hadoop has become the poster child for delivering scalable analytic powers that meet today’s big data requirements, and companies are biting at the opportunity to benefit from that potential.
Yet with the growing buzz surrounding Hadoop so comes the skepticism. While it would be ludicrous to doubt the value of data and its ability to create high-resolution observations and interpretations about how businesses are performing, it’s time to ponder how to bring big data technologies, such as Hadoop, into the next phase of efficiency and utility. In order to do that, we must understand what’s driving the skepticism that’s out there, and how to address it.
Who’s Jumping on the Hadoop Bandwagon?
Looking at the big data landscape, one of the obvious observations is the increasing number of startups focused on Hadoop. When you have a unique shift in the market like the one brought on by big data, it’s inevitable that startups will want to jump on the bandwagon. If there’s a great opportunity, Silicon Valley and the world of emerging technology will always try to capitalize on it.
With all of this hype, people question whether there is a growing Hadoop bubble and ahead-of-time expectations. We’ve seen Hadoop-related companies leave the gates with initially promising growth numbers and then stagnate early on. People are starting to question if Hadoop is worth all the fuss.
Those looking at the Hadoop landscape need to recognize whether there’s value creation in the company or if it’s a matter of unlimited funds that’s being used to buy growth. There are Hadoop-related companies that create tremendous value, have solid bookings and revenue numbers — that is where the potential lies. On the flip side, there are also companies where growth is mostly bought — that is where the potential dies.
Bring Something New to the Hadoop Game
The companies that are giving rise to the doubts around the promise of Hadoop are …read more
It’s been 20 years since I was “the new Guy.”
Hello friends and colleagues. I wanted share some thoughts after my first 90 days at Hortonworks. It’s been a thrill ride to say the least, there is all of the normal new guy / first impression stuff – and for those of you who know me, you know I am very sensitive to all that!
Working with our founders and engineering team has been a blast. Seeing the passion in their eyes, feeling the energy and enthusiasm in their voice, has been inspirational. Their unbridled dedication to our new compute and open source paradigm is evident and infectious.
It is clear that we are at the center of multiple inflection points.
First, the open source paradigm will continue to reshape how software is developed. Leveraging a community of brilliant people means constant innovation. It also means that these talented people actually compete to find the best solutions and approach to data management problems—and the real winners are users of Apache Hadoop and HDP.
Second, it is really about the platform. Providing the first real solution for quickly landing very large and very diverse data, Hadoop along with the broader ecosystem provides the ability to capture data that used to go to waste. This collective pool of information is the raw material for refined and advanced analytics that will drive improved business models.
Meeting our customers and prospects has also been quite revealing. These are companies who are redefining their industries by being data centric and data driven. Along the way, I’ve heard some common themes.
At the Hadoop Summit in June, we had a customer panel comprised of some real thought leaders. They all mentioned in their comments that the best thing they did was getting started. The sooner you start collecting and making broad and diverse data available to data scientists and business analysts, the sooner the value shows up. And, while it may seem ‘salesy,’ it’s actually the point. Today’s modern data architecture turns the normal IT projects upside down. Schema on read is the opposite of traditional models, and very relevant today. Big data and sources of big data evolve and change so rapidly that it’s only possible to glean value by landing and analyzing.
“We’ve only just begun.”
The new and innovative use cases are being invented now, taking advantage of the new ‘land it first’ mentality. From …read more