From the course: Learning Data Analytics: 1 Foundations

Getting started with data projects

From the course: Learning Data Analytics: 1 Foundations

Getting started with data projects

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- [Instructor] Here are a few best practices for any data analyst. First of all, there is no guesswork in data. If you do not know the answer, do not make one up. I tell my new analysts that the day of guessing is officially over for them. I encourage people to answer with things like, let me confirm, or I can get that information. Don't send your manager off thinking one thing only to discover you were way off. There is no dialing it back. People will react to the information that you give them, and they believe you're providing them the answer, not a guess. Don't publish a talking point with data until you have vetted it and verified it. You can do a few of these verification steps yourself, and I'll share that a little bit later in this course, but it never hurts to have a peer review. The more senior the people on your team, the more they'll appreciate the fact that you went that extra mile to ensure accuracy. I'm sure all of us have been to meetings where people were not prepared for the meeting, and we need to use our time effectively because we don't have a lot of it. It's so easy when everyone is together for all of that time to be gone. Be sure you ask to be on the agenda. Let people know you need just a few minutes to gain clarity or get feedback. Take notes of everything in relationship to the objective. Sometimes people who have the information are hard to reach, and when you have time with them, and they're giving you that information, be sure to make notes on it. It can be frustrating when people come into meetings and they start presenting information and there's no setup and no context behind what they're presenting. So I encourage people to provide some details about what you'll be presenting so that when they're getting the first view of it, they can understand it. It's also helpful when you provide that detailed information, when they review it after the meeting, they can have that information as a primer before they dive in. I like to use Word documents and simply list where the data came from, key definitions of things that they may see and other information that might be relevant for them so they can get the most out of the data. I have been in so many meetings where data analysts just throw data up on the screen and dive in, and it will make the presentation way harder than it needs to be. Do not eat up critical time that you need for followup by just diving in on screen. When you have a lot of ground to cover, use a slide deck to help guide you through. That deck will keep you on track. It also ensures that you've covered all of your key points without getting sidelined by people looking at your data as you've just dove in on the screen. I learned pretty early on in my career that people need time to process and digest the things that I'm showing them. I have to reiterate the key points while they're looking at what's on my screen. I remind presenters all the time, tell them what you're going to tell them, tell them and then tell them what you've just told them and give them time to understand and process so they can ask valid questions. So my last best practice is keep in mind it's never a bad idea to ask other professionals their best practices.

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