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Big Data

Data Quality Terms Defined

October 31, 2014 by Martin Doyle

Data quality.

After 20 years developing data quality solutions, the team at DQ Global are very familiar with data quality terminology. However, many customers tell us that data quality terms can be confusing. What is the difference between enrichment and enhancement? And why do we cross match or automate in our quest for clean data?[read more]

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Where Do You Draw the Line Between Relevancy and Privacy?

October 30, 2014 by Tamara Dull

The Big Data MOPS Series. 

We have a love/hate relationship with ads. Whether they’re on television, in our favorite publications, or online, we love them if they’re relevant and interesting, or get annoyed when they get in the way of [insert whatever we’re doing]. I have to admit: I rarely watch a television show in real-time anymore. I’ll record a show, wait 20+ minutes, and “chase the show” with the recording—ad-free.[read more]

Data Rights as Law? Meet the Montana Legislator Turning Theory into Policy

October 30, 2014 by Tracey Wallace

Big data policy.

From politicians to tech evangelists to just your everyday citizen who is paying attention to all the data news out there, everyone has an opinion when it comes to data rights, ethics and what businesses or governments should be doing to enforce proper collection and use.[read more]

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Big Data: 25 Amazing Need-to-Know Facts

October 28, 2014 by Bernard Marr

The Big Data Guru column.

We surely see a lot of hype surrounding big data but I believe the following 25 facts speak for themselves and help to paint a realistic picture of the phenomenon we now call ‘Big Data’ - a phenomenon that is changing the world as we know it.[read more]

The Journey to Big Data Literacy: 9 Must-Read Books to Discover Your Inner Data Scientist

October 28, 2014 by Tracey Wallace

The Human Face of Big Data

If you have relatively low big data understanding or knowledge, like the vast majority of us, then here is your way in, your ticket to thought leadership[read more]

Could Big Data Be the Cure for the Largest Ebola Outbreak Ever?

October 24, 2014 by Mark van Rijmenam

Big data and Ebola.

Anonymous data to track a possible outbreak is a lot different than knowing which cell phone owner has symptoms of Ebola, if they have replied to a warning message. What should be done if this is known and it can be seen that he or she travels across the region or has a lot of contact with others?[read more]

7 Big Data Blunders You're Thankful Your Company Didn't Make

October 24, 2014 by Trips Reddy

Big data blunders.

When it comes to big data, learning from experience often means losing customers. Instead, let the other guys do the bidding for you, and learn from their mistakes.[read more]

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4 Ways Hadoop Is Improving Our Healthcare System

October 24, 2014 by Sameer Nori

Hadoop in healthcare.

With new medical advances every day, it’s no surprise that the healthcare field has a bold new technology that allows doctors and researchers to more easily access and learn about diseases, treatments, and cures. This technology, Apache Hadoop, is a big data storage and processing platform that gives healthcare providers the ability to effectively use much more data than has ever been possible.[read more]

Data Quality: Cash Drain or Cash Gain?

October 23, 2014 by Martin Doyle

Cash drain.

According to a 2009 Gartner study, businesses estimated that they are losing an average of $8.2 million per year because of poor data quality. Five years on, we are storing, managing and relying on more data than ever before. It’s more important than ever to mitigate the risk of poor data quality by investing in solutions that work.[read more]

Smart Cities Technology: Opportunities for Midsized Vendors

October 22, 2014 by Julie Hunt

Smart city.

The term 'smart city' is becoming familiar around the world as urban areas realize that a great deal of benefit can come from connecting physical and digital worlds to better serve the needs of citizens and the administration of the city. A smart city doesn't just result from changes in infrastructure and technologies – it must embody new ways of thinking and planning.[read more]

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Addressing 5 Objections to Big Data

October 22, 2014 by Gil Allouche
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Objections to big data.

For many businesses, especially smaller ones, big data can be almost incomprehensible and understandably so. There are so many different parts to it that if you take one look you may think it’s just too much for your business to ever use. Again, this is where big data in the cloud is so important.[read more]

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The Big Data Capacity Crisis

October 21, 2014 by Bernard Marr
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The Big Data Guru column.

With the amount of data being generated worldwide increasing at a rate of 40%-60% per year (depending on who you believe), some people certainly think so. The EMC Corporation’s Digital Universe 2014 report states “data is growing so fast there are bound to be difficulties ahead.”[read more]

How to Compare Business Intelligence Cloud Costs and Features

October 20, 2014 by Jason Bowden

BI cloud features.

As an IT provider, I am overwhelmed with all the options for Business Intelligence in the cloud and very confused by how to compare service offerings in order to effective provide the best solutions. In the article we will discuss some of the different offerings on the market and why all business are racing toward the cloud for Business Intelligence Solutions.[read more]

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How to Create Users in Oracle BI (OBIEE) and WebLogic Tutorial

October 15, 2014 by Julie Johnson

Oracle BI.

This short guide will take you through the process of creating new users in Oracle OBIEE and WebLogic as well as introducing security concepts including the use of security groups and application roles to control data access.[read more]

Data Integration Is the Schema in Between

October 14, 2014 by MIKE20 Governance Association

Data integration.

The third of the five biggest data myths debunked by Gartner is big data technology will eliminate the need for data integration. The truth is big data technology excels at data acquisition, not data integration. This myth is rooted in what Gartner referred to as the schema on read approach used by big data technology to quickly acquire a variety of data from sources with multiple data formats.[read more]

 

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