Big Data Research
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Big Data Research
The latest research and anaysis on trends and issues related to Big Data. Analytics, BI, security, and privacy implications are curated
Curated by Kevan Huston
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Informatica makes first step to transforming data inside Hadoop » Ovum

Informatica makes first step to transforming data inside Hadoop » Ovum | Big Data Research | Scoop.it

Hadoop benefits elusive for typical enterprises; Informatica hopes to change that:

 

"Informatica takes an important baby step towards bringing data transformation inside Hadoop, a development that will lower the barriers for enterprises wishing to tap the power of MapReduce processing in working with unstructured or variably structured big data. Informatica may not be the first vendor to develop tooling for processing and it certainly won’t be the last, but the release of its new HParser tool is an important step in making Hadoop a more civilized platform for the enterprise."

 

More: http://ovum.com/2011/11/03/informatica-makes-first-step-to-transforming-data-inside-hadoop/

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Big Data, MapReduce, Hadoop, NoSQL: The Relational Technology Behind the Curtain

What are the boundaries to big data? Is the future bright for relational databases? Good questions to ask.

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12 Top Big Data Analytics Players -- InformationWeek

12 Top Big Data Analytics Players -- InformationWeek | Big Data Research | Scoop.it

When data grows into the tens or even hundreds of terabytes, you need a special technology to quickly make sense of it all. From Hadoop to Teradata, check out the top platform options.

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How Yahoo Spawned Hadoop, the Future of Big Data | Wired

How Yahoo Spawned Hadoop, the Future of Big Data | Wired | Big Data Research | Scoop.it

“There’s a change happening, driven by unprecedented volumes and velocities of
unstructured data. Traditional relational databases and business intelligence
software can’t handle this. The thesis is that Hadoop can.”

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Hadoop, Business Analytics and Beyond - Wikibon

Hadoop, Business Analytics and Beyond - Wikibon | Big Data Research | Scoop.it

A Big Data Manifesto from the Wikibon Community:

 

"From storage and server technology that support Big Data processing to front-end data visualization tools that bring new insights alive for end-users, the emergence of Big Data also provides significant opportunities for hardware, software, and services vendors. Those vendors that aid enterprises in their transitions to Big Data practitioners, both in the form of identifying Big Data use cases that add business value and developing the technology and services to make Big Data a practical reality, will be the ones that thrive.

 

Make no mistake: Big Data is the new definitive source of competitive advantage across all industries. Enterprises and technology vendors that dismiss Big Data as a passing fad do so at their peril and, in our opinion, will soon find themselves struggling to keep up with more foreword-thinking rivals. For those organizations that understand and embrace the new reality of Big Data, the possibilities for new innovation, improved agility, and increased profitability are nearly endless."

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IBM discusses bringing big data applications to businesses - ZDNet (blog)

Enterprises are recognizing the potential for leveraging the web sources for broader business intelligence, as well as their internal content, according to David Barnes, program director of emerging Internet technologies for the IBM Software Group.

 

The traditional type of analytics platforms that we’ve run in the past might have created what we wanted or wasted our time, Barnes argued. He posited that the next wave of analytics and big data is concentrated on content-centric web apps with longer running data collection and analytics.

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How Amazon uses big data to prevent warehouse theft

Today at the Web 2.0 Summit, Alyssa Henry, VP of Amazon’s AWS Storage Services, gave one example of how Amazon uses its cloud storage and processing power to handle one issue that is little thought about but vital to its overall profitability: combatting warehouse theft.

 

To determine which items are most likely to be stolen, Amazon stores the product catalog data in S3, which ends up having more than 50 million updates a week. The team spins up Amazon compute clusters every 30 minutes, crunch the data, and the data is fed back to the warehouse and website. At the center of the service is the new Elastic Map Reduce, a new hosted Hadoop framework running on AWS that lets customers spin up the equivalent of a supercomputer for processing big data.

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