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Best Practices


Digi-lution: How Online Data Can Indicate Civil Unrest

April 15, 2014 by Philip Cohen


Saying that the Internet is a medium for change, knowledge, discourse, or even civil unrest is a vast understatement, because it's actually a fundamental medium for these things. As much as a decade ago, different countries, politicos, and countries used the Internet to either launch change or to censor and staunch people pushing change.[read more]

Forget Big Data, We Need Smart Data [VIDEO]

April 14, 2014 by Lachlan James


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]

How Data Will Make Air Travel Safer

March 25, 2014 by Travis Korte

Safer airtravel with better data.

Airlines and air traffic controllers use a lot of information to keep passengers safe, integrating weather readings, physical information about the plane, passenger data, and other kinds of data. But as the uncertainty surrounding Malaysia Airlines Flight 370′s disappearance confirms, better information and ways to act on it will be crucial for the future of air safety.[read more]

Architecting Big Data Solutions

March 12, 2014 by John Sanders

Big data solutions.

In this article I would like to outline, at a high level, the overall thought process for "architecting" big data solutions. The process of developing an architecture is a very personal thing. I don't propose to say that this is the only way - this is simply a framework from which you could launch your own effort.[read more]


6 Simple Steps to a Big Data Strategy

March 5, 2014 by Bernard Marr

The Big Data Guru column.

We now live in a world in which the volumes of data are exploding by the second. While some companies are leveraging these data assets very well to generate mouth-watering competitive advantages, most are completely overwhelmed by the amounts of data they are generating and are simply scratching the surface of the other, external data they could use.[read more]


Technology Training Needs a Hands-On Approach

March 4, 2014 by Paul Barsch

Risky Business column.

Instead of simply a “core dump” of manuals and online training courses, technical employees should also get “hands on” simulations, boot camps and courses led by advanced robo-instructors to fully hit the ground running[read more]


Micro-Social Networks: Data with Context

March 1, 2014 by Jean Dobey

Micro-social networks.

For most consumers, social media has become the go-to source for entertainment, news, reviews and much more. The ever-increasing amounts of data shared through social media, however, have made it difficult to find the right information at the right time. A staggering 4.75 billion items are shared by Facebook users daily.[read more]


The Use and Abuse of Big Data and Hadoop

February 26, 2014 by Rick Delgado

Privacy vs. big data.

Big data analytics is having a huge impact on us all. The ability to collect, store and analyze massive amounts of disparate data---using analytics platforms such as Hadoop in the cloud to uncover hidden connections, correlations and insights---is playing a bigger role than ever in influencing almost every aspect of our lives.[read more]


Sales Pipeline Management Dos and Don'ts

February 4, 2014 by Thomas Oriol

Sales pipeline management.

There are lots of sales methodologies in the market. As the makers of award-winning sales pipeline analysis and forecasting application SalesClic, we are familiar with most of them. Here are, distilled in a list of dos and don’ts, their main prescriptions.[read more]

Guiding Principles for Data Enrichment

January 29, 2014 by Bob Lambert

Data enrichment.

The data integration process is traditionally thought of in three steps: extract, transform, and load (ETL). Putting aside the often-discussed order of their execution, "extract" is pulling data out of a source system, "transform" means validating the source data and converting it to the desired standard (e.g. yards to meters), and load means storing the data at the destination.[read more]

Customer Experience Innovation: Aligning Business with Customer

December 20, 2013 by Julie Hunt

Aligning business with customer / shutterstock

Organizations must recognize that management doesn't mean attempting to control and dictate to the customer what the 'experience' will be. Agile and effective business processes are instrumental to providing a sophisticated means to respond well to customer needs, while navigating many complex variables, moving from customer to customer.[read more]

Turning Decision Making Into a Game

December 19, 2013 by MIKE20 Governance Association

decision making / shutterstock

Organizations are more complex today than ever before, largely because of the ability that technology brings to support scale, centralisation and enterprise-wide integration. One of the unpleasant side effects of this complexity is that it can take too long to get decisions made.[read more]

SAS Coding: Scattered Data Might Need CPORT Procedure Help

December 17, 2013 by Tricia Aanderud

Scattered data syndrome got you down?

Forget about big data issues – I had scattered data issues. It’s a syndrome common to those who create everything on the fly with no thought of reuse. After hearing all my scattered data drama, Ken decided I needed a central storage location and he created a file server. All of the environments can reach it.[read more]


Enterprise Data Trends to Watch for in 2014

December 13, 2013 by Philip Cohen

What are the enterprise data trends for 2014?

Since different departments and employees able to access enterprise data instantaneously, in-the-moment analyses of problems or new projects is easier, as is providing better and more specific customer service. Here are some enterprise data trend predictions for 2014.[read more]


The Opportunities and Challenges of Big Data

December 12, 2013 by Lee House

big data storage issues / shutterstock

Data management has its difficulties, and companies today are finding this out the hard way as they face increasing challenges managing data they have accumulated for years. Big Data requires storage, and most companies are not equipped to meet such demands. This puts a burden on firms big and small.[read more]