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Data Quality

Is Your Company Ready to Deploy Business Intelligence Intelligently?

April 22, 2014 by Ray Major

Ready to deploy BI?

Although the majority of data-driven enterprises may have or use BI software or systems, a recent survey we took of IT executives revealed that there is a vast difference between having BI and using BI to the company’s full advantage. There is an even larger chasm between the cost to implement BI and the value realized from those efforts.[read more]

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The Billboard Problem: Why Intelligent Ads Only Live Online, for Now

April 18, 2014 by Samantha Meckler

Billboard.

For centuries, billboard ads have been an ambiguous but undoubtedly treasured way to convert eyeballs into customers. Data-driven business decisions are becoming the way of the world -- and no longer just in theory, so 'guessing as proof' metrics will continue to be exactly what they always have been -- ambiguous and nostalgic.[read more]

Disaster DIY: The Argument to Build or Buy Data Integrity Controls

April 17, 2014 by Kristen Paral

It’s a question of “build versus buy” and the answer is fairly straightforward. When it comes to end-to-end data accuracy – not to mention valuable reporting and dashboard tools – building your own software to monitor data integrity could be a Disaster DIY project of its very own.[read more]

Data Collection Made Simple [VIDEO]

April 17, 2014 by Tracey Wallace

Simple data collection.

Activation apps put the power of smart data collection into the hands of executives, while maintaining user security and privacy. The concept is simple: allow companies to utilize social authentication absolutely anywhere they so chose to collect identity data information in less than half and hour, and without having to involve a tech team.[read more]

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]

Why Data Quality Is of Utmost Importance in Information-Centric Organisations

April 1, 2014 by Mark van Rijmenam

Data quality.

High quality data will lead to valuable information and insights for your organisation, but obtaining high quality data is easier said than done. Improving your data quality and sustaining a good quality data output should be at the centre of your Big Data Strategy.[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]

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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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]

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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]

The Top of the Data Quality Bell Curve

January 22, 2014 by MIKE20 Governance Association
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Data quality bell curve.

“Information is the value associated with data,” William McKnight explains in his book Information Management: Strategies for Gaining a Competitive Advantage with Data. “Information is data under management that can be utilized by the company to achieve goals.” Does that data have to be perfect in order to realize its value and enable the company to achieve its goals? McKnight says no.[read more]

Your Data Quality Wish List [Part Two]

January 17, 2014 by Gayle Nixon

Make a wish. A data wish.

For the second installment of our data quality “Wish List” series let's tackle another common concern from data professionals, “I wish I knew how poor data quality was manifesting itself in my business.”[read more]

Data Quality Chill Factor

January 15, 2014 by MIKE20 Governance Association

Data quality.

The recent North American cold wave that winded its way across Canada and the United States. This polar vortex also spun the phrase wind chill factor into almost every conversation, prompting me to investigate how wind chill is calculated, and leading me to yet another cold contemplation of data quality.[read more]