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Choosing Your Business Intelligence Solution: Don't Be Afraid of the “Smoosh-ins®”

Friday, May 31, 2013

Great short article by SmartData Collective on how with BI you should be able to have your cake and eat it too

When an enterprise selects a BI solution, it should be able to get the combinations of BI functionality that best meet the varied needs of different communities.


Getting exactly what you want is a principle that was most deliciously embodied by Steve’s Ice Cream, an institution beloved by Boston-area college students beginning in 1973. Steve pioneered the “smoosh-in,” adding customer-selected goodies like crushed Heath Bars® and M&Ms® to his rich, slow-churned ice cream. (Now you can buy ice cream like this in any grocery store, but in the 1970s you had to wait in line at Steve’s Somerville store.)

Like the original Steve’s ice cream, BI is best when you pick and choose.

So why do Enterprise IT groups often standardize on the equivalent of a pint of vanilla when selecting hardware and software products? There is a variety of reasons:

  • Lower costs -- there is only one tool to learn, use and support
  • More expertise -- they can develop more expertise by concentrating on one tool
  • Potential lowered licensing costs
  • Better vendor support -- “one neck to choke” (a phrase that I hate)

When choosing a BI solution, the IT group typically goes through a software evaluation or “bake-off,” selecting tools based on who scores the most across a multitude of criteria. The winner is typically a full-stack BI vendor because it has the most extensive feature checklist and when you add up the scores it has the highest number. In addition, enterprise IT groups will use the ratings from industry research analysts to justify their selection. (The analysts themselves likely went through a feature checklist selecting the most feature-rich product.)

An enterprise’s business community will have a very diverse set of analytical needs and work styles. The type of analysis they perform will vary based on the depth, subject, volume, and structure of the data used, as well as the business processes: examining salespeople’s performance, providing customer support, predicting customer behavior, etc. Business people will also approach analysis differently based on their background and experience.

Read the rest of the article here

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