This may be the most easily understood habit for me, and if you’ve read this blog previously, you’ll find it a recurring theme here. Whether it’s having the foresight to plan ahead and architect the data warehouse (instead of just fulfilling the basic requirements), building it to incorporate slowly changing dimensions, determining the most effective grain of your tables, working to capture better data at the source, proactively cleansing data before it loads, or ensuring your ETL is done right every time, I harp on the basics of this philosophy quite a bit ( I could easily link several more articles, but I’m trying to get you to read this one first). With that, I’m going to tell you a story.
Recently, my family made a trip to Disney World. It’s a bit of a trek for us, so the first goal was to get us there. Our first decision was to determine how long we wanted to go for, and my wife and I agreed that 5 days in the parks was about all we wanted to handle for this trip. We priced it out, including plane tickets, and from there, we were able to determine what our budget would be. I know some of you are saying, “Wait a minute – you have that backwards! You take your budget and figure out what you can afford first!” Habit #2 says that’s a load of Grade A Oscar Mayer bologna. The premise of habit #2 is to imagine what could be, not limit yourself to what you think is possible today. My wife and I set a goal for ourselves – 5 days at Disney World with the kids, and only then did we worry about how we were going to achieve it. If we looked at the budget first, we would have automatically limited ourselves as to what we could achieve. Disney World bills itself as the place where dreams come true, and that’s exactly what we did. Because we started with the dream, we were inspired to achieve it, and we did. Covey talks about all success being twice created. The first is imagined and created in the mind, while the second is achieved when it is created physically.
It’s no different for data workers. Far too often, we simply fulfill the requirements placed on us by business consumers. The problem with this is that the business consumers usually don’t know the advanced functionality we could provide with our software packages, and as such, the requirements we are given ends up with us doing a data dump to Excel for our business end users to spend hundreds of hours analyzing and manipulating. This greatly reduces our value add to the company, and reduces the value of the joy brought to us personally when we know we are working on something important and complete a job well done. It’s literally a lose-lose proposition, and yet data workers throughout the process continue to do it every day. By taking the time to ask, “Why?” of our business consumers, we can often “upsell” them to a better solution for their needs. Best of all, it’s usually more fun to create and often is far less easier to maintain than a heavily formatted PDF or Excel with hundreds of thousands of records for them to search. The solution is simple. At the start of the project, ask the questions so you can figure out where the business is going, and only then do you provide them with the road map and a framework on how they can get there.