This blog was originally posted to the Piraeus Consulting blog on November 24th, 2015 and may contain out-of-date information.

BI in Layers

This is an exciting and difficult time in Business Intelligence. The tools available are advancing at a breathtaking rate while best practices are changing equally as fast. While the tools promise to take in data and output insights, what that process requires can be somewhat vague at times. Usually, the programs are designed to tackle one of these four layers:

  1. Raw Data
  2. Data Transformation
  3. Data Model
  4. Visualizations

Oftentimes when businesses struggle to produce results from their BI strategy it is because they try to use one tool to accomplish everything, when the tool is really designed to tackle only one of the four layers.


The Visualization Layer

Let’s focus on ways to maximize insights in the visualization layer. This layer is interesting because it is where the final usable form of insight is communicated to business users, thus delivering return on investment from business intelligence. At this layer, data handling strategies meet business strategies to produce value. Numerous solutions for this layer exist on the market today with more to come.

For now, I will focus on Tableau because it is currently the clear leader in terms of execution in the visualization layer.


Explore Ideas Rapidly using Iterative Visualizations

Since we have divided BI into four layers and have the expectation of using different solutions for each layer, we’ll work with Tableau because the ability to execute is paramount.

It is well understood that Tableau is designed for easy use by non-technical users. However, what people sometimes don’t understand is that ease of use by business users is not only a nice feature of Tableau, but also a critical component of an effective Tableau deployment.

I think oftentimes businesses don’t give themselves enough credit for the expertise they hold. Departments are made up of people with years of experience in their fields, and the companies they work for have hired them for a reason: they are smart! These are the people companies want solving problems directly. So, it is critical they are the ones using a solution like Tableau directly.


Insight – What Everyone is Really After

Insight occurs when a solution appears unexpectedly after several attempts to solve a problem. When used directly by business users, Tableau will create the conditions required for insight in two ways:

  1. Faster Iteration Cycles – More attempts for a solution to suddenly appear.
  2. Business Experience is Combined with Raw Data – The ultimate solution is unexpected. Business users will just know it when they see it, while analysts with less specific knowledge may not.

More iterations + More exposure to information = More opportunities for people to generate insight.

With that in mind, here are three ways to position Tableau within your organization to maximize insights:

  1. Iteration is paramount. Maximizing the volume of questions people can answer is really important. The visualizations should provide answers to business questions, not push the frontier of visual design on a consistent basis.
  2. Encourage the business experts themselves to get directly involved in creating visuals, even if that means tricking people by creating alluring reports that will entice them to make a few more clicks on their own.
  3. Encourage people to conduct meetings directly in the tool and try to avoid PowerPoint decks. Weekly meetings between team members are discussions between experts to solve problems, and are more effective than presentations.

Ultimately a Business Intelligence solution will only provide a return on investment if it is providing valuable information – hence the name intelligence. Thinking of your solution in terms of layers will ensure that you are able to choose the best tool available to solve each piece. Involving business experts in the visualization process will increase both the likelihood of and the opportunities for insight, which drives value and closes out the investment.


By: Karlen Rothenbueler | Associate, Analytics