In this video, learn best practices how to get started.
- [Instructor] Throughout your career, you'll hear a lot about best practices and using them but let me assure you it's super important on any data project that you follow any best practices that you learn. There's nothing more dangerous than guesswork when it comes to research and data. Make sure you work with your team to vet your results before you publish anything. Be prepared for there to be a verification process, but if there's not a process, be sure you ask for peer review. This is especially important if you're reporting on information in new systems. It's so easy to get lost in the weeds of a meeting or spend too much time in one area and not enough in another area.
Be sure to keep a proper agenda of what you need to present to your team. You may not be in charge of the agenda, but the person who is needs to know how much time you need and what you need to discuss. I can't say this enough, if a data analyst is not taking a million notes, then they're setting their self up for failure. Your access to all your team members may be limited to just meetings. Be sure to keep notes on all the follow-up questions you may have. If your work is complicated, which data often is, then be sure you build documentation that supports the consumer of the information.
Teams often work at different times, and having a handy document from their favorite analyst goes a long way. Last but not least, everyone on earth needs skills training and updates. We are creatures of habit, for sure, but spending a little time on your own skills will help you stay on top of your game.
- Defining data analysis
- Understanding the data analyst role and other roles
- Identifying data, data fields, and data types
- Learning syntax
- Finding existing data
- Cleaning data
- Data best practices
- Working with business data
- Charting data
- Building pivot tables and charts
- Using Excel for data analysis