When you first read this title you probably think these are instructions for someone else—but not you—right? But read on—see where you’re at when it comes to the issues of talking, listening, moderating and overall meeting etiquette.

Business Intelligence guru, analyst and author, Wayne Eckerson, and I had great times when we worked together at The Data Warehousing Institute (TDWI). Although we have both moved on to other ventures, we remain in touch and I still like reading his books and articles.

I particularly enjoyed the first chapter of his most recent book, Secrets of Analytical Leaders: Insights from Information Insiders, where he talks about the concept of “purple people.” But before I explain that, read this concept from Wayne in his book.

Have you ever wondered how it would feel to stand on the top step of an Olympic podium, lean over and have a gold medal placed around your neck? You not only have family, friends and coaches cheering you on, you have a whole nation behind you. It must be an overwhelming moment. While few ever have that opportunity, you can be the go-to champion in your organization. How can that happen?

Like most of you, I work in the corporate world. I’ve been around long enough to be part of good teams and bad teams. I have also had the opportunity to build teams. Building a team is challenging and a lot of hard work. Being on a bad team is a stressful nightmare. Building a bad team is, well, a long story. If you did it once, you’re probably no longer with that company. With most companies, you are either a player or you are a coach (boss). If you’re self-employed that can be the most challenging—because you’re both.

I am also a big football fan. High school, college, professional, fantasy—I like all of it. I never played on the field myself but I love watching a great game at any level. As the season winds down at this time of year, I always get a little sad that it will be eight months before I get to watch my favorite teams again.

Starting in the late 1970’s and continuing throughout the decade of the 1980’s, one of my favorite football coaches was Bill Walsh.

In the early 1990’s I was working for a small software company in Seattle that developed mainframe database performance monitors. One day it was announced that we were being acquired by a much larger company. It was the first time in my career I had faced an acquisition and the horror stories I heard from co-workers were unsettling to say the least.

To be honest, the entire experience turned out to be relatively uneventful and even positive. I was able to work with great people who taught me a lot. I clearly remember one afternoon when my new boss chatted with me informally at a corporate retreat and simply asked, “Do you consider yourself a manager or a leader?”

Think about that for just a minute and ask yourself how you would answer that question.

As a much younger writer and marketing guy watching the database technology boom of the 80’s and 90’s, I was fascinated with the advent of the data warehouse surge that started about twenty years ago. I saw it coming and watched it bloom. The promise of a “sandbox of meaningful data” for quicker and easier use by line of business managers was exciting.

The total cost of operations (TCO) of Business Intelligence (BI) systems is often measured in three categories: time-to-completion of projects, on-budget completion of projects, and cost per user of BI applications. There is a key process in every project that impacts all three categories: Business Requirements Engineering.

An effective requirements methodology ensures that project scope is clearly understood and costs accurately estimated. At the same time, when we deliver what users want, usage and adoption of the solution increase the user base. Why then do so many programs not take a closer look and the effectiveness of their approach to this key part of the process?

BI Professionals are used to working with a wide range of products and platforms and typically have a pretty substantial tool belt to be able to work across a multitude of different technologies. Over the past couple of months I took the opportunity to experiment with technologies that are entering the data warehousing ecosystem. These technologies included the Cloudera Sandbox, Hortonworks Sandbox, IBM Big Insights Sandbox, and Amazon’s Red Shift.