Hadoop Isn’t For Everyone, But There Are Cloud-Based Big Data Solutions For Us All

James Staten
If you think you can do big data in-house, get ready for a lot of disappointment. If the data you want to analyze is in the terabytes in size, comes from multiple sources -- streams in from customers, devices or sensors -- and the insights you need are more complex than basic trending, you are probably looking for a data scientist or two. You probably have an open job requisition for an Hadoop expert as well and have hit the limit on what your capital budget will let you buy to house all this data and insights. Thus you are likely taking a hard look at some cloud-based options to fill your short term needs.
 
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Predictions For The Data Economy In 2015

Gene Leganza
The data economy — or the system that provides for the exchange of digitized information for the purpose of creating insights and value — grew in 2014, but in 2015 we’ll see it leap forward significantly. It will grow from a phenomenon that mainstream enterprises view at arm’s length as interesting to one that they embrace as a part of business as usual. The number of business and technology leaders telling us that external data is important to their business strategy has been growing rapidly -- from one-third in 2012 to almost half in 2014.
 
Why? It’s a supply-driven phenomenon made possible by widespread digitization, mobile technology, the Internet of Things (IoT), and Hadooponomics. With countless new data sources and powerful new tools to wrest insights from their depths, organizations will scramble to use them to know their customers better and to optimize their operations beyond anything they could have done before. And while the exploding data supply will spur demand, it will also spur additional supply. Firms will be taking a hard look at their “data exhaust” and wondering if there is a market for new products and services based on their unique set of data. But in many cases, the value in the data is not that people will be willing to pay money for bulk downloads or access to raw data, but in data products that complement a firm’s existing offerings.
 
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Where Is IBM’s Sweet Spot In Asia Pacific?

Tim Sheedy
Over the past few years, IBM has certainly copped its fair share of criticism in the Asian media, particularly in Australia. Whether this criticism is deserved or not is beside the point. Perception is reality — and it’s led some companies and governments to exclude IBM from project bids and longer-term sourcing deals. On top of this, the firm’s recent earnings in Asia Pacific have disappointed.
 
But I’ve had the chance to spend some quality time with IBM at analyst events across Asia Pacific over the past 12 months, and it’s clear that the company does some things well — in fact, IBM is sometimes years ahead of the pack. For this reason, I advise clients that it would be detrimental to exclude IBM from a deal that may play to one of these strengths.
 
IBM’s value lies in the innovation and global best practices it can bring to deals; the capabilities coming out of IBM Labs and the resulting products, services, and capabilities continue to lead the industry. IBM is one of the few IT vendors whose R&D has struck the right balance between shorter-term business returns and longer-term big bets.
 
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Moneyball, Big Data, And The Data Scientist

Mike Gualtieri

Ari Kaplan is a real moneyball guy. As President of Ariball, he has worked with more than half of all the MLB organizations to evaluate players for maximum return on the baseball club's investment. But, Ari is much more than just a moneyball guy, he is also a computer scientist, a data scientist, and has the business acumen to produce dramatic results for the teams he works with. He is the real deal. Forrester TechnoPolitics caught up with Ari at Predictive Analytics World in Chicago to ask him how Big Data and the role of the data scientist will advance the science of moneyball. 

About Forrester TechnoPolitics

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What Is A Data Scientist?

Mike Gualtieri

Why all the fervor about big data? The answer is that it provides deep insights and predictive models that can dramatically improve business outcomes. But you need a data scientist to get there. There’s a lot of mythology about what a data scientist is and isn’t. In this episode of TechnoPolitics, Mike Gualtieri explains what a data scientist is, what skills they need, and how to hire one. You may also be interested in What Is Hadoop.

About Forrester Instant Insight

Navigating the fast changing world of business technology is a constant challenge. Forrester Instant Insight aims to provide simple, complete answers to some popular questions. Our goal: You will watch the video and be enlightened in 5-minutes or less.

This Forrester Instant Insight was produced by Mike Gualtieri and edited by Lindsay Gualtieri