EMA Blog: Business Intelligence and IT Management

In skiing, the “black diamond” run or ski slope is often referred to as “high risk/high reward.” You receive lots of “reward” skiing the black diamond slopes, but you have a significant amount of “risk” associated with variable terrain, such as the presence of trees and the possibility of injury. However, the black diamond slopes are very fun to experience, and you can mitigate the risks with preparation, practice, and a really good skiing helmet.

Waaay back in the day (say 2002), organizations would ask themselves:

As I review my series of #100linesOnBIDW blogs over the last couple of weeks, I found myself looking at the Data Management posting. I covered when to apply schemas, Big Data, and data governance. What I left out was technical implementation concepts for data management systems like row vs. column orientation; in-memory vs. spinning disk primary storage; and symmetric multiprocessing (SMP) vs. massively parallel processing (MPP). Processing and storage were the “developments” of 2012. I left 2013 for the “how to use” Data Management platforms.

If I told you in September that the Baltimore Ravens would win the Super Bowl in February and you did nothing with that information ( i.e. place a bet, announce your prognostication skill, etc. ), was my prediction worth anything? Much like “if a tree falls in the forest and no one is there to hear it, did it make a sound?”, you need action from a piece of analysis, prediction, etc. to make it worthwhile.

Albert Einstein once said:

Edward de Bono, a noted expert on creative thinking, once said:

When Aesop created the fable about the shepherd boy who cried wolf, the message was clear:

“Back in the day”, Pablo Picaso once said:

I have always loved the song “88 Lines about 44 Women” by the Nails.  And based on some recent success with a blogging topic relating to the songs of the 80s, I thought that I would continue that theme with “100 Lines about 25 Business Intelligence Topics”. Think of this list, or series of lists, as a wide ranging set of predictions, topics for discussion and observations relating to the business intelligence and data warehousing domain for the upcoming year.

Next week, EMA and 9sight will hold a webinar covering our Big Data research findings.  Among our insights will be that Big Data has evolved. Moving forward, Big Data isn’t: