Data Management is a dirty job

Dirty JobsImage via WikipediaOne of my family's favorite shows is Dirty Jobs with Mike Rowe.

The premise of the show is they profile jobs that are less than glamorous, and highlight the people that are not afraid to get dirty in their daily jobs.

As the show begins, Mike introduces the people he will be working with, then they describe the task at hand. Once Mike gets an overview of the job he dives in and tries his hand at the job. The purpose of this, of course, is entertainment. Mike is not a specialist in any of the jobs, yet he goes through a bit of training and then tries his hand. Mike has a great sense of humor and it shines through as he attempts to do the jobs in the show. Sometimes he is successful, sometimes his attempts are less than successful.

Either at the end of the segment, or throughout the segment, Mike attempts to understand and explain to the audience how doing such a job impacts the bottom-line of the business. For example, why is it important to this company to scrape out a refuse container? Well, if it gets too clogged it can cause damage to the machinery which will prevent the machines making the products the company sells.

As I watch these shows, I am reminded both of my time as a consultant and my roles as an architect in the various positions I have held. As a consultant one of the things that you have to do very quickly is to understand the business processes of what you are working on. Why is it important that the performance of this particular query be improved? If we don't get an answer to this question quickly it will delay our orders which ultimately impacts delivery of products to our customers.

The day to day work done as a data warehouse architect or business intelligence architect is quite a bit different from the activities that Mike Rowe does on his show, but in essence aren't they similar?

We look at the details of business processes, delve into the dirty details of how transactions are processed and data is accumulated, then present that data to as many people as we can through the front-end tools that we deploy. There are times when we spend many hours working on a particular problem of how to process and present a concept easily and in a repeatable manner.

Diving into the details of how a business runs can be a "dirty" job in that there are many details that must not be overlooked. In that sense, data management itself is a dirty job because so many people take for granted that when they look at a report, or a dashboard, that the data is clearly presented. We make it easy for data to be presented in a clean manner, but the details of how it got there is anything but clear to the majority of people within an organization.
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