From the course: Introduction to Career Skills in Data Analytics

Presenting data challenges effectively to others

From the course: Introduction to Career Skills in Data Analytics

Presenting data challenges effectively to others

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- There are some moments in meetings where I realize no matter how simple I make what I say next, all of the sudden people are going to be staring through me, trying to figure out what in the world I'm talking about. That's tough. It shouldn't be like that in every meeting. And if it is that way for you every time you talk about data, then you need to focus on communication skills. Again, a very important soft skill for a data professional. I find that talking to leadership through the process can really help their understanding of what we're working with on a data project. Here's an example. The data team has been tasked with studying a scenario that will have a major impact on the organization, and it's imperative that we get this right. It's a high stakes project. They've provided us all the access to the data, all the questions they need answered, and we have our approach and we're ready to go. In the first several passes of the project, we realize one of the key pieces of information that we need for the study has not been collected consistently. And there appears to be major gaps in the time for the data we do have, and it really makes us question if we can trust the data. What do you do facing this scenario? I can tell you very easily what not to do. Do not wait to communicate the challenges and make sure you're prepared to discuss them. Here are a few ways you can address this situation. Be sure to let the right person on the team know what data appears to be missing. People make mistakes. It could have been a bad file or even a missing file. Also communicate about what you see in the data you do have. This gives you an opportunity to confirm that they understand about the gaps you're finding in the data, this way there's no big surprise. And by the way, they may have a very sound reason for those gaps. You may just not know about it. This is part of the learning curve of any new data set. There are other scenarios. The organization is hoping that the data team will be able to show something very positive with the data, and you found the exact opposite to be true. This is truly a challenging scenario and not a fun one to face. So what do you do? When I find myself in this situation where there is a totally different understanding of the data reality versus the actual reality, I start by confirming that I'm not missing something. I double check everything. I confirm that I've not introduced an error in any way. If I find that this is the truth of the data, then I turn to the person in leadership and discuss my findings to get further insight into what I may be missing and get guidance from them on the next steps for me to take. Remember, we don't have access to all the data or even all the knowledge. Turning to your leadership is the legitimate next step. If you discover no errors, you have done all that you can have and the truth isn't going to be exactly what they planned. Having some communication skills on how to deliver information might be your next step. Remember, data is used to inform a business for improvement and sometimes delivering the results can be hard. As a data professional, just make sure you have thoroughly checked all your results, follow the chain of command of information, and by all means, communicate with your team.

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