Amazed as I am at how much time has passed since I first wrote the article below and how much more varied experience I’ve been able to gather since then, I’ve yet to discover a case where most of these tips wouldn’t prove relevant
It has now been 6 months since I started studying at Tilburg University and for that time I’ve been able to meet a number of great and most inspiring people. One of them, and the conversation we had in particular, sent me in quiet contemplation for a couple of hours.
Upon hearing that I had worked as a Reporting Analyst for a couple of years before coming to Tilburg to pursue my master degree, he asked me for any tips and tricks I might have for a person who would like to start working in the field.
So, here they are:
1) Know your data sets and data peculiarities, know what each field actually shows, so that when you get a new reporting request, you know what to take to produce a relevant picture
2) Know the business processes behind the data: this will help you understand your stakeholders better and ultimately better anticipate their reporting needs. “Forewarned is forearmed” and “A stitch in time saves nine” do hold true in the world of reporting. Any data consolidation, or reformatting that you can anticipate and do at the time of report generation may easily save you a few sleepless nights after a new reporting request has come in.
3) Before creating any new report/analysis, take the time to map out its data flow. As time consuming an effort this may be initially, it will pay off in the long run by making it easier to spot opportunities for enhancement and to respond to change requests in a few months.
4) Automate whenever possible: not only does it save time but also minimizes error rate. And a low error rate gains acceptance of you and of the quality of your analyses/recommendations among your key stakeholders and decision makers.
5) Keep extensive version history and report documentation: chances are that one day you would want to explore greener pastures and then woe to your replacement (and to you before you leave) if you don’t have all the documentation in place
6) Compile/Consolidate generated data in MS Access: this will make it way easier and feasible to restate generated data, should business conditions/relationships change and you have to provide a picture of what has been happening for the past 3 years
What do you think makes a good data analyst?