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Business Intelligence, or BI, has been around for a very long time. First used in the 1950s, the term has come a long way and really started gaining mainstream attention in the late 1990s. Since then, it has been used to describe everything from a single Microsoft Excel worksheet to much more complex items such as Analytical Performance Management, Geospatial analytics, and Non modeled exploration and In-memory analytics (to name a few). Are you as confused yet?
The primary reason for this blog post is to share what our experience (aka the real world) has taught us on how to practically implement BI for our clients. I’ll do my best to keep this short-and-sweet, because in all honesty there’s plenty to say on this topic, and enough BI buzzwords and statistics to confuse the entire island of Manhattan!
Our firm, C5 Insight, primarily works with three platforms (SharePoint, Dynamics CRM and Salesforce.com) that all perform some flavor of BI. In working closely with our awesome clients, we have learned that it’s not always the technology that causes Analysis Paralysis, but often it’s the very term “Business Intelligence.” After digging into this more, we realized that the term often has the connotation of a complex, multi-tiered OLAP data-warehouse that will take a team of 12 data architects to implement. Understandably, to clients this equals more time to implement, which ultimately equals more money to spend. That alone stops many businesses in their tracks and prevents them from ever touching BI. Starting now, let’s not call it Business Intelligence (BI), let’s call it Data Visualization (DV). In fact, I really like Vitaly Friedman’s definition of this:
“The main goal of data visualization is to communicate information clearly and effectively through graphical means. It doesn’t mean that data visualization needs to look boring to be functional or extremely sophisticated to look beautiful. To convey ideas effectively, both aesthetic form and functionality need to go hand in hand, providing insights into a rather sparse and complex data set by communicating its key-aspects in a more intuitive way. Yet designers often fail to achieve a balance between form and function, creating gorgeous data visualizations which fail to serve their main purpose – to communicate information."[1]
I’ve bolded the two phrases that really stand out to me. In our experience, this is what most of our clients are trying to achieve. Of course, we do have large clients that have very large data-warehouses with teams of data architects, but by and large, this is exactly what most are looking for – I know it is certainly true of our firm. So with "Data Visulization (DV)" as our new term, what does this mean for you? I’m glad you asked! Below are three steps that we hope will help get your organization pointed in the right direction to simply do something with the data and insight that you already possess – in essence, attain BI (the term your boss uses) through fairly simple DV (the term you are now using).
My hope is that this blog post, and these three items in particular, will help you take a step back and get started with something today. We all know this, we’ve been taught it all of our lives (How to eat an elephant, baby steps, one foot in front of the other, day-by-day, etc.). If you have any questions regarding this post or our services, please contact us. Also, leave us a comment to tell us if this post has helped you get started and what you are building!
References: 1. http://www.smashingmagazine.com/2008/01/14/monday-inspiration-data-visualization-and-infographics/
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