Posts Tagged ‘analytics’

Break the cycle of deploying unwieldy Hadoop infrastructure

Chris Harrold

CTO Big Data Solutions at EMC
Chris is responsible for the development of large-scale analytics solutions for EMC customers around emerging analytics platform technologies. Currently, he is focused on EMC Business Data Lake Solutions and delivering this solution to key EMC customer accounts.

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We are in a new data-driven age. With the rise in adoption of big data analytics as a decision-making tool comes the need to accelerate time-to-insights and deliver faster innovation informed by these new data-driven insights.

You know what? That’s a lot of mumbo-jumbo. Let’s boil it down to the real issue for IT: the tools that analysts and data science professionals need were not really designed to be enterprise-friendly, and they can be unwieldy to deploy and manage. Specifically, I’m talking about Hadoop. Anything that requires the provisioning and configuration of a multitude of physical servers (that are exactly the same) is always going to be the enemy of speed and reliability. More so when those servers operate as a stand-alone, single-instance solution, without any link to the rest of the IT ecosystem (the whole point of shared nothing). Shared nothing may work for experimentation, but it is a terrible thing to build a business on and to support as an IT operations person.

How do I know this? Because I have been that guy for 25 years!

In order to bridge the gap between data science experimentation and IT operational stability, new approaches are needed to provide operational resiliency without compromising the ability to rapidly deploy new analytical tools and solutions. This speed in deployment is essential to support the needs of developers and data scientists. But the complexity and unwieldy nature of traditional Hadoop infrastructure is a major barrier to success for big data analytics projects.

Consider these questions and see if they sound familiar:

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The Next Stage for Strata Hadoop World and Big Data

David Dietrich

Director of Technical Marketing in Big Data Solutions at EMC
David Dietrich is the Director of Technical Marketing for the Big Data Solutions group at EMC – a group that provides technology and services solutions to customers with needs related to Big Data and data science. Prior to this role, Mr. Dietrich was head of data science education at EMC, where he developed three courses in data science for practitioners, heads of teams and executives.

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Strata + Hadoop World New York is an event I look forward to attending each year.  I like the sessions, speakers, and also seeing how the attendees and vendors have evolved over time.  When I first began attending SHW 4 or 5 years ago, the attendees were only about 200 people, and this year in NYC they topped 6,300!   As a result, the conference has had to move from the New York Hilton to the Javits Center, since it is such a huge event now.

As with Big Data itself, focusing on the sheer volume of conference attendees doesn’t tell the whole story.  Here are a few of my observations from the conference.

  1. Early majority now joining the fray. As I mentioned, I’ve attended Strata for 4-5 years, and knowing that others also return every year, I expected more attendees at the sessions around emerging technologies that are gaining adoption, such as Spark or Kafka.  Although this did occur, I underestimated the heavy attendance in sessions for people just attending Strata for the first time.  This means the ‘beginner’ sessions were packed, for every person who’s been using Hadoop for years and now wants to experiment with Spark, there are still scores more trying to learn R or learn how to deploy Hadoop in a feasible way.

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What Are The Real Effects Of Climate Change?

Mona Patel

Senior Manager, Big Data Solutions Marketing at EMC
Mona Patel is a Senior Manager for Big Data Marketing at EMC Corporation. With over 15 years of working with data at The Department of Water and Power, Air Touch Communications, Oracle, and MicroStrategy, Mona decided to grow her career at EMC, a leader in Big Data.

Contributing to social good is now literally at everyone’s fingertips. That is why EMC and Earthwatch Institute have teamed up to encourage citizens to become data collectors, or citizen scientists. Through the collection of more data sources, data scientists can better uncover how climate change is affecting plants and animals by altering the timing of key natural events.

This collaboration is called the Whenology project, with the first study underway to investigate how climate change is affecting raptor migrations at Acadia National Park. To create awareness and encourage more participation, EMC launched a microsite that provides educational materials, track progress, and report insights.

whenology

I spoke with EMC Distinguished Engineer John Cardente about the Whenology project and it’s potential to provide a powerful citizen science platform for collaboratively tackling virtually any large-scale, high impact societal issue.

1.  What is the Whenology project and what are your major objectives?

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Hadoop Summit 2015 Reflections

Chris Harrold

CTO Big Data Solutions at EMC
Chris is responsible for the development of large-scale analytics solutions for EMC customers around emerging analytics platform technologies. Currently, he is focused on EMC Business Data Lake Solutions and delivering this solution to key EMC customer accounts.

Latest posts by Chris Harrold (see all)

Big Data - Hadoop Summit 2015

Before the ink has even really dried on Hadoop Summit15 in San Jose I am sitting down in a rare moment of peace to write out some reflections from my experience and what I have seen from the sessions, keynotes, partners, and users here at the show.

Hadoop Gets Real

The most lasting impression I got from the overall theme of the show and the people in attendance was that Hadoop is not an “emerging tool” anymore. The momentum, use cases, and indeed the buzz of attendees was that there is massive adoption and momentum built up in the marketplace. Behind this wave of early adoption is a lot of pent-up demand that is waiting for things to stabilize and become more enterprise ready. Once the tooling around the Hadoop ecosystem is more robust, and the platforms that it runs on are more operational, there is no limit to the demand that this ecosystem can produce.

In counterpoint to this fact, there is another countercurrent of theme that Hadoop is not “all things to all people”, and so there is a lot of discussion around the emergence of the logical successor to Hadoop as the analytics tool of record. Certainly the buzz around Spark is indicative that this is the way of the future and ties into the second theme of the show that I observed in numerous conversations and sessions.

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