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Thoughts on analytics, data management, visualization and collaboration

Archive for July, 2010

–Dr. Strangelove and Excel

Posted by Brett Sheppard on July 29, 2010

Dr. Strangelove or: How I Learned to Stop Worrying and Love Excel

With Microsoft’s new PowerPivot capabilities, and spreadsheet user interfaces to data sets in Hadoop by IBM BigSheets and Datameer, spreadsheets are more viable than ever as an analytics and business intelligence (BI) tool, to the consternation of some BI program managers.

At Gartner BI Summit 2010, in April in Las Vegas, Gartner advised BI advocates to give up trying to wean business users off Excel, and instead accept that Excel is here to stay. Sri Vemparala, manager of reporting and BI at Stanford University, told Craig Stedman at TechTarget “No matter what we try to do, I don’t think we can get away from Excel.” Gartner analyst John Hagerty advises IT departments to follow a rapid-iteration model to create and update reports, and allow business users to decide how to deploy data, whether in BI software interfaces, dashboards, Excel, SharePoint or other collaboration tools.

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Posted in Big Data | Tagged: , , , , | 4 Comments »

–Next LAMP Stack

Posted by Brett Sheppard on July 27, 2010

 

The Next LAMP Stack: Hadoop Platform for Big Data Analytics

Editor’s note: a shorter version of this article appeared on GigaOM.

Many Fortune 500 and mid-size enterprises are intrigued by Hadoop for Big Data analytics and are funding Hadoop test/dev projects, but would like to see Hadoop evolve into a more fully integrated analytics platform, similar to what the LAMP (Linux, Apache HTTP Server, MySQL and PHP) stack has enabled for web applications. For example, head of technology strategy and innovation at credit card giant Visa, Joe Cunningham, told the audience at last year’s Hadoop World that he would like to see Visa’s use of Hadoop evolve from an alpha/beta environment into mainstream use for transaction analysis, but has concerns about integration and operations management.

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Posted in Big Data, Hadoop | Tagged: , , , , | 6 Comments »

–Karmasphere Releases

Posted by Brett Sheppard on July 25, 2010

Making Hadoop Accessible for Enterprise Developers and Analysts

Karmasphere offers front-end client software that enables developers and analysts who are not necessarily Hadoop specialists to develop, debug and deploy Hadoop jobs to virtually any private, public or hybrid Hadoop cluster. You can download the NetBeans or Eclipse versions of the no-cost Karmasphere Studio Community Edition, or apply for a limited beta of the just-announced Karmasphere Studio Professional Edition and Analyst Edition, at Karmasphere’s software download page. Editor’s note: This is a reprint of an article that first appeared on Big Data News.

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Posted in Big Data, Hadoop | Tagged: | Leave a Comment »

–Accel Event Recap

Posted by Brett Sheppard on July 22, 2010

Hadoop, Memcached and Solid-state Storage

Hosted at Stanford University, Accel Partners brought together executives from four of their portfolio companies to discuss evolution of a “New Data Stack” incorporating Hadoop, memcached and sold-state storage. Read the rest of this entry »

Posted in Hadoop | Tagged: , , , , , , , , | Leave a Comment »

–The Big Data Imperative

Posted by Brett Sheppard on July 22, 2010

World Data Volumes in the Zettabytes

With enterprise data volumes moving past terabytes to tens of petabytes and more, business and IT leaders face significant opportunities and challenges from Big Data. While IDC estimates that global data volumes have already reached multiple zettabytes, we’re seeing just the beginning of the Big Data era.

What constitutes Big Data is relative, and varies by organization. Big Data presents “significant design and decision factors for implementing a data management and analysis system.” (O’Reilly Radar Release 2.0, Roger Magoulas and Ben Lorica, February 2009). For a large enterprise, Big Data may be in the petabytes or more, while for a small or mid-size enterprise, data volumes that grow into tens of terabytes can become challenging to analyze and manage. Read the rest of this entry »

Posted in Big Data | 1 Comment »

 
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