Analytics is booming, and there is a gap between the supply of skilled analysts and the high demand in the market. In the U.S., the first comprehensive analytics program was established in 2007. Prior to that, existing programs focused on the components of analytics - statistics, information technology, data mining and business intelligence. It took another four years before other U.S. schools picked up on the trend and started slowly supplying students with advanced analytics degrees.

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A Prerequisite for On-time Analytics Projects

By Diego Klabjan, Aug 01, 2012

Needless to say, there can be no analytics project without data. A project starts by identifying data, cleansing it, performing analytics, and then conveying the results or solutions. The rule of thumb is that 70 to 80 percent of the total timeframe for an analytics project is spent on data preparation and a much smaller portion to actually conducting the analytics.

There are many reasons why analytics software projects routinely miss deadlines and overrun the budget, in particular regarding the data preparation phase where leaders kick these projects off without nailing the prerequisites:

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Fortune 500 companies are big enough, and have enough resources, to assemble and run their own internal analytics teams. In today’s environment, it is becoming impossible for a large corporation to succeed without employing analytics. The situation is completely different if we make a step down to small and medium business (SMBs), which are typically corporations with less than 500 employees and revenue in hundreds of millions of dollars. Most SMBs do not have enough resources to deploy an internal analytics team. But lack of resources is definitely not the prohibitive argument for why they don’t use analytics.

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