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Data Warehousing

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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]

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Is Big Data Under Threat by New Internet Magna Carta?

April 1, 2014 by Bernard Marr

The Big Data Guru column.

Big data can deliver mouthwatering value to companies and society, but the NSA revelations about spying on people as well as allegations that large corporations are snooping on customers has tainted the reputation of big data analytics. A growing number of people are now calling for a new Magna Carta for big data, but would that spell the end of the big data movement or a new beginning?[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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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]

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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Facebook's Big Data: Equal Parts Exciting and Terrifying?

February 18, 2014 by Bernard Marr

Big Data Guru column.

This post looks at the gigantic big data repositories Facebook is creating and discusses the exciting as well as terrifying opportunities to exploit that big data. The question is, does big data analytics put too much power in the hands of a commercial company like Facebook?[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]

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How MapR’s M7 Platform Improves NoSQL and Hadoop

January 31, 2014 by Michele Nemschoff

MapR’s M7 platform.

M7 removes the trade-offs organizations typically face when looking to deploy a NoSQL solution. Here’s a look at how the M7 platform is making NoSQL and Hadoop easier, faster and more dependable. Since enterprises already have several disparate data systems, having the ability to unify NoSQL and Hadoop under a single scalable cluster eliminates data silos and provides administrative simplicity.[read more]

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8 Features of a True Enterprise-Grade Platform for Hadoop and NoSQL

January 30, 2014 by Michele Nemschoff

True enterprise-grade platform for Hadoop and NoSQL.

Businesses have several options when looking for a Hadoop and NoSQL solution. The advantage of using the right enterprise-grade solution is that it can provide the dependability, ease-of-use, and speed required for real production use.[read more]

Guiding Principles for Data Enrichment

January 29, 2014 by Bob Lambert

Data enrichment.

The data integration process is traditionally thought of in three steps: extract, transform, and load (ETL). Putting aside the often-discussed order of their execution, "extract" is pulling data out of a source system, "transform" means validating the source data and converting it to the desired standard (e.g. yards to meters), and load means storing the data at the destination.[read more]

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7 Ways Businesses are Leveraging Hadoop

January 25, 2014 by Michele Nemschoff

Leveraging Hadoop.

When you hear about Hadoop or Big Data, you probably think of large Internet companies, such as Google or Facebook. However, the use of Hadoop is not limited to large search engines or even Internet marketing. Take a look at seven striking examples of how businesses across many industries are leveraging Hadoop to reach multiple business goals.[read more]

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Can Big Data and Hadoop Feed the World?

January 24, 2014 by Michele Nemschoff

Feed the world.

It’s no secret that the world’s population is growing. In fact, by 2050 the world’s total population is expected to reach the 9 billion mark, and according to the United Nations’ Food and Agriculture Organization, food production needs to increase by 60 percent by 2050 in order to keep up with population growth.[read more]

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3 Reasons Hadoop is Heading to the Cloud

January 9, 2014 by Michele Nemschoff

Hadoop is heading to the cloud.

Cloud computing and big data have been vying for the attention of business owners for several years now. Both initiatives are compelling, as big data analytics promises the potential of powerful new business insights, and cloud computing offers greater flexibility, productivity and cost-savings in running IT systems traditional on-premise systems.[read more]

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Google and Apache Hadoop: A Match Made in the Cloud

January 7, 2014 by Michele Nemschoff

A match made in... the cloud.

Running Hadoop on Google Compute Engine leverages the power and efficiency of Google’s data centers to execute at scale and solve large problems. Utilizing the Google Cloud Platform, enterprises have the flexibility to expand or contract the cluster size on demand to provision precisely the amount of resources required to meet their data processing needs.[read more]

The World's Most Unusual Data Centers [INFOGRAPHIC]

January 6, 2014 by Mark van Rijmenam

Underwater data centers?

With an ever growing amount of data in the world, that data also needs to be stored and why not storing that data in an unusual location? Whoishostingthis has released an interesting infographic that shows some of the world’s most unusual data centers in the world.[read more]