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Data Warehousing

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Beware of Big Data Technology Zealotry

June 23, 2014 by Paul Barsch

Risky Business column.

Invariably, there are hundreds of additional arguments proffered by big data vendors and technology zealots inhabiting organizations just like yours. However, there are few crisp binary choices in technology decision making, especially in today’s heterogeneous big data environments. Beware big data zealots that counsel you otherwise.[read more]

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Creating a More Efficient Data Center

June 16, 2014 by Cameron Graham

Efficient data centers.

Once you start thinking about how much electricity it takes to power the servers that house all this information, the sheer magnitude becomes clear. To put it in perspective, one large data center can use as much electricity as a small town. What constitutes a “large” data center? A typical data center may be over 15,000 square feet.[read more]

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WOW! Big Data at Google

June 3, 2014 by Bernard Marr

The Big Data Guru column.

Google has not only significantly influenced the way we can now analyze big data (think MapReduce, BigQuery, etc.) – but they probably are more responsible than anyone else for making it part of our everyday lives. I believe that many of the innovative things Google is doing today, most companies will do in years to come.[read more]

Agile Data Warehousing

May 19, 2014 by Benjamin Harden
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Data warehousing.

The most common thing I hear is that you can’t build a warehouse using Agile because it is impossible to iterate over a data model. Modeling changes are going to happen regardless of the delivery methodology so learning to deal with change is important even if you are delivering in a waterfall environment. If change is going to happen, why not embrace it early and make it part of the way you work?[read more]

Inventory Analysis: Affordable, Available, Actionable

May 18, 2014 by Richard Thelwell

Inventory analysis.

For any manufacturer or distributor, the problem with inventory management is easily stated. Simply put, there’s often too much of the stuff that isn’t selling—and far too little of the stuff that is selling. The result? Disappointed customers, stockouts and lost sales—combined with shelves groaning with inventory that nobody wants.[read more]

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Five Things You Must Know About Data Warehouse Automation

May 1, 2014 by Ian Nicholson

Data warehouse automation.

Data Warehouse Automation tools are becoming more mainstream now for their obvious benefits:- Fast delivery times, lower cost of development, better decisions being made sooner. At last, businesses are waking up to the fact that waiting three to six months for a Business Intelligence project to complete is no longer acceptable.[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]

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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]