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Data Warehousing

Outsourcing, Off-shoring and Near-shoring – what works or doesn't for BI & DWH

May 14, 2012 by Shaughn Knight
with 57 views
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Well, the unique selling point of any outsourcing vendor is their customer testimony. The published customer testimonial will show you only an ideal picture of the vendor’s perfection and not the failed projects. Practically failed projects of a vendor are tough to be identified. [read more]

Refuse to be a Cloud data hostage.

April 27, 2012 by Ephraim Cohen
with 46 views
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Most people agreed that, philosophically, Vogels was right – nobody wants to be pay big bucks just to be held hostage to a cloud vendor, regardless of whether it was for IaaS, Paas, or SaaS. For that matter, nobody wants to have to pay big bucks to break free, either! [read more]

How To Develop A Top-Notch Data Warehousing System

April 26, 2012 by Brett Stupakevich
with 154 views
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Processing data in a well-developed data warehousing system provides the competitive edge that companies are striving for. The question then becomes: What steps should you take to ensure you build a data warehouse that enhances and supports the decision-making process? [read more]

Three Ways HR Analytics Can Boost the Bottom Line

April 25, 2012 by Brett Stupakevich
with 257 views
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Tim Ringo, a partner in London-based Maxxim Consulting, notes in a recent blog post for Harvard Business Review that many corporations are still using hunches or gut feelings instead of data analytics to make the tough calls related to HR. [read more]

Data Design Principles

April 23, 2012 by Justin Hay
with 213 views
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Taking a practical approach to developing a well-formed enterprise data warehouse – and by that, I mean one that is accurate, efficient and productive – involves basing it on sound design principles. [read more]

Big Data Q&A for the Data Protection Law and Policy Newsletter

April 19, 2012 by Jeff Jonas
with 175 views
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I have been given permission to re-publish an interview I did with the Data Protection & Law Policy newsletter. Also to appear in the e-Finance and Payments Law & Policy newsletter. May be of interest to some of my readers. [read more]

When Do You need All the Data for Big Analytics?

April 19, 2012 by David Smith
with 188 views
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Norman makes the argument that while sampling and aggregation are often useful ways of handling very large data sets for statistical analysis, there are nonetheless several situations where using all of the data in the analysis is beneficial and/or important. [read more]

Improvement Project for Services; Remember You're Never Really Done

April 13, 2012 by Jay Arthur
with 63 views
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While define, measure, analyze, improve and control (DMAIC) lead most people to believe they need to start by defining and measuring something, data about the number or cost of these types of defects are already collected somewhere by someone. Find the data! As described in my previous article about Control Charts for Services, get the data into a format that can be graphed as a control chart. [read more]

Listening In: Big Ideas About Big Data

April 11, 2012 by Brett Stupakevich
with 476 views
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National Public Radio is not the most obvious place for a deep dive on “The New World of Massive Data Mining,” so it may have surprised listeners when the April 2 edition of Diane Rehm’s popular NPR discussion program devoted an hour to just that topic. But the wide-ranging conversation covered some fascinating territory, and attracted thoughtful questions from the audience. [read more]

“Something is not Right!” – Don’t Ignore Your Gut When Analyzing Information

April 9, 2012 by Mike Urbonas
with 142 views
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What the classic children's book "Madeline" has to do with analyzing, and questioning, information - and how to avoid a corporate culture that over-emphasizes hard data to the point of employees feeling compelled to ignore their 'gut', their intuition, that something is not right. [read more]

Impressions of SAP HANA

April 9, 2012 by Mark Bradbourne
with 776 views
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Bottom line, if you’ve got the budget dollars, and the highly managed data in your source systems then you can make a strong argument to bring HANA into your environment. On the other hand, if you have data challenges around quality or master data management you should probably address those issues first before a major investment like HANA because you won’t see the ROI. [read more]

The Fallacy of the Data Scientist Shortage

April 1, 2012 by Neil Raden
with 1,164 views
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Photo by justgrimes via Flickr

The shortage of data scientists to handle big data is overblown. Much of these activities are currently practiced, albeit without Hadoop and some other recent innovations. But the simple truth is that even data scientists spend a good portion of their day doing things that can be done by others. In addition, the demand for data scientists is hardly even across industries and those that require these skills already have them or know how to get them, either through employment, 3rd party analytics providers, purchased apps or consulting. [read more]

Big Data Showcase: Advanced Analytics

March 30, 2012 by Alex Olesker
with 328 views
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Carahsoft’s Government Big Data Forum also had two showcases to highlight the actual solutions available for dealing with massive amounts of complex data and getting the most out of it for your agency or enterprise. [read more]

Information Management Technology Revolution and Research Agenda for 2012

March 19, 2012 by David Menninger
with 126 views
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In recent years the complexity of information management has risen dramatically. The volume of information being processed has increased exponentially and so have the challenges of ensuring consistency and quality and managing governance and the information life cycle. New data types and sources such as comments on social media have emerged and must be integrated into an organization’s information assets. [read more]

Moving BI off the Mainframe

March 15, 2012 by Doug Lautzenheiser
with 357 views
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The magic sauce to mainframe modernization comes in the form of the Micro Focus Enterprise Server, which basically provides a mainframe replica on a cheaper box. One major benefit is that mainframe Job Control Language (JCL) batch processes can be ported as-is to a mid-range computer. Differences between the mainframe and the new platform are hidden under the covers. [read more]

Why Large Enterprises and EDW Owners Suddenly Care About Big Data

March 13, 2012 by Smart Analytics
with 237 views
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Before investing money in buying commodity hardware and calling consultants to wave the big data magic wands, companies should do a lot of soul-searching because once you set the wheels in motion, it is likely to take up lot of your organization’s focus. [read more]