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Forget Big Data, We Need Smart Data [VIDEO]

April 14, 2014 by Lachlan James

BI.TV

The interactive portion of this episode directs your attention towards two thought-provoking discussions taking place on LinkedIn. The first conversation was instigated by the question “Why do BI implementations fail?” and can be found on the Business Intelligence Professionals Group.[read more]

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A Complete Guide to Overcoming Executives’ Concerns about Hadoop

April 13, 2014 by Michele Nemschoff
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Overcoming executives’ concerns about Hadoop.

CEOs are often critical of adopting new technology, and for good reason. New technology is expensive and all too often fails to come through and offer any real value to the company. This could present a challenge for IT managers who want to implement Apache Hadoop, the increasingly popular and cost-effective framework for large-scale, data-intensive deployments, into the company’s technology infrastructure.[read more]

No, Hadoop Is Not Going To Replace Your Data Warehouse

April 11, 2014 by Timo Elliott

Hadoop and your data warehouse.

The real opportunity of new technologies like Hadoop and In-Memory processing is to enable new, more flexible, analytics-focused, actionable applications. And that takes much more than just a platform. Organizations want best-practice business applications capable of analyzing big data and putting it in the hands of people on the front line of your organization that need it, via cloud and mobile devices.[read more]

Defining Business Intelligence 3.0

April 11, 2014 by Lachlan James

Business intelligence 3.0.

So what exactly is Business Intelligence 3.0? Is it a mass of meaningless marketing messages, a collection of multiple BI advancements, or does it represent a single technological shift that many have misconstrued? Well, according to Bill Cabiro, it’s none of the above. Cabiro contends that BI 3.0 represents two things: A changing philosophy regarding BI user types and an amalgamation, or confusion, of terms.[read more]

Cloudera Makes Hadoop a Big Player in Big Data

April 7, 2014 by Mark Smith

Big data analytics. 

Cloudera’s executive team has the co-founders of Hadoop who worked at Facebook, Oracle and Yahoo when they developed and used Hadoop. Last year they brought in CEO Tom Reilly, who led successful organizations at ArcSight, HP and IBM. Cloudera now has more than 500 employees, 800 partners and 40,000 users trained in its commercial version of Hadoop.[read more]

How Text Mining Can Help Your Business Dig For Gold

April 5, 2014 by Seth Redmore

Text mining.

Your customers want to communicate with you. Humans communicate in a wide variety of ways – body language, eye movement, intonation of speech, hand gestures, use of color and clothing. There is no system on earth that can yet capture all of the wide bandwidth of communication that we all use, as we go through our days.[read more]

Thoughts on the Future of Hadoop in Enterprise Environments

March 29, 2014 by Timo Elliott

Hadoop in enterprise environments.

The elephant in the room. It’s now clear that Hadoop will play a key part of your future enterprise architecture. But how will it integrate with existing infrastructures and other new technologies? As Hadoop matures beyond pixel-only business models (social websites, online video games) and inexpensive data storage it is being forced to embrace — and learn a few lessons from — the enterprise systems that drive real-world business.[read more]

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How Your Hadoop Distribution Could Lose Your Data Forever

March 27, 2014 by Michele Nemschoff

Hadoop distribution could lose your data forever.

Relational database users have long depended on foundational protection techniques, such as data replication and snapshots. Today, both are also implemented in standard Hadoop architectures. Their method of application and effectiveness, however, is not the same across distributions.[read more]

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How To Maximize Performance and Scalability Within Your Hadoop Architecture

March 13, 2014 by Michele Nemschoff

Hadoop.

One of the main reasons for moving away from a traditional database solution for managing data is to increase raw performance and gain the ability to scale. It may come as a surprise to you to know that not all Hadoop distributions are created equal in this regard.[read more]

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6 Simple Steps to a Big Data Strategy

March 5, 2014 by Bernard Marr

The Big Data Guru column.

We now live in a world in which the volumes of data are exploding by the second. While some companies are leveraging these data assets very well to generate mouth-watering competitive advantages, most are completely overwhelmed by the amounts of data they are generating and are simply scratching the surface of the other, external data they could use.[read more]

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3 Big Hadoop Myths Dispelled

March 4, 2014 by Michele Nemschoff

Hadoop myths.

As with any new technological innovation, a lot of myths have been generated about Hadoop. At Strata + Hadoop World, held in NY at the end of October, Jack Norris, CMO of MapR, discussed three of those myths and how MapR dispels them.[read more]

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Technology Training Needs a Hands-On Approach

March 4, 2014 by Paul Barsch
5

Risky Business column.

Instead of simply a “core dump” of manuals and online training courses, technical employees should also get “hands on” simulations, boot camps and courses led by advanced robo-instructors to fully hit the ground running[read more]

What Does a VC Look for in a Big Data Startup? [VIDEO]

February 27, 2014 by Todd Nevins

Big data and venture capital.

Venture Capital firms and Angel investors pumped in over $3.6 billion into Big Data startups in 2013 and investments this year are expected to top this figure. Jake Flomenberg started writing code and managing products with Lockheed Martin and Cloudera before moving into a role with Splunk.[read more]

7 Important Types of Big Data

February 26, 2014 by Michele Nemschoff
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Types of big data.

Big data is a term thrown around in a lot of articles, and for those who understand what big data means that is fine, but for those struggling to understand exactly what big data is, it can get frustrating. There are several definitions of big data as it is frequently used as an all-encompassing term for everything from actual data sets to big data technology and big data analytics.[read more]

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NoSQL Vs. RDBMS for Interactive Analytics: Leveraging the Right and Left Brain of Data

February 6, 2014 by Soren Riise
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NoSQL Vs. RDBMS.

Comparing NoSQL and relational databases is lot like comparing the left and right sides of the brain. Too much focus on structural differences and attributes can overshadow the fact that we’re stuck with both sides of the brain and we need both to make the best use of sensory data.[read more]