From the course: Complete Guide to Analytics Engineering

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Data visualization best practices

Data visualization best practices

From the course: Complete Guide to Analytics Engineering

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Data visualization best practices

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- [Instructor] This is the end of our chapter on Tableau. We could honestly go through 20 to 30 more topics on Tableau. It's a really broad tool with lots of cool and unique ways to bring data to the stakeholders. I chose the contents of this chapter since they're the most common task you encounter as an analytics engineer and should be a good foundation to start. If you want to learn more Tableau, you could check out Curt Frye or Heidi Kalbuh's courses, here on LinkedIn Learning. Their courses are focused only on Tableau, and therefore go much more in depth. But before we move on to our last chapter of analytics engineering, I want to share a few more BI best practices to keep in mind when building visualizations through any tool, whether it be in Python and Tableau, Power BI, Qlik, Looker, or even Excel. These tips will help make your visualizations more powerful. The last thing we want is to go through the whole lifecycle of data, spend hours of development time, and then lose the…

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