Visualizing time-series data is one of Tableau's best and defining features. Tableau provides a flexible method for visualizing dates so you can easily display chronological values and compare time periods.
However, with that flexibility comes a lot of a lot of options which can feel overwhelming and complex. For instance, why are there two different ways to visualize months and what's the difference? What does that mean if a date pill is green versus blue?
Parameters are a powerful tool in Tableau. They allow your end user to customize the view that they're seeing by selecting your pre-defined parameter values.
But where do we begin when using parameters? Well, the "Swap-A-Field" Parameter is the perfect place!
Tableau Prep is a powerful tool for cleaning, structuring and preparing data for analysis in Tableau Desktop. The Tableau Prep Builder software provides the ability to create data workflows which can be run manually. That's fine when data is updated infrequently, but it doesn't work well when data needs to be refreshed every day or every hour.
When you put a single measure on the color tab in your Tableau worksheet, you get a single color legend. That makes sense.
But sometimes it can be frustrating. For instance, what if two different segments of your business have significantly different Sales values?
How often do you build a Tableau dashboard and feel like it has too many filters? This happens to me all the time! You don't know what to do with them, right? Make two rows of filters? Ugh. Make a massive column? That's a lot of screen real estate. Add show/hide buttons so users can toggle a layout container on and off the page? That doesn't seem ideal either. What if someone doesn't realize they can show filters?
Donut Charts are a very visually-appealing chart type, used to show part-to-whole relationships. They’re simple and effective, and are a great tool to add to your dashboarding arsenal. While they’re not a built-in chart type in Tableau (unlike a bar chart, pie chart, or line graph), we can build them with a few extra steps!
Let's say you want to filter a Tableau worksheet to only contain data from the latest date in the data set. That's pretty simple if the latest date is consistently today or yesterday. You can just use a relative date filter! But what if the most recent date in the data set is less consistent?…
Getting the structure of our data correct for Tableau Desktop can make a huge difference. Tableau is pretty picky about the way it wants our data to be formatted. Generally, each column should be a new dimension or measure.
Joins in Tableau Desktop are one of the primary methods for combining multiple tables of data horizontally. One of the great things about joins are their flexibility! You can choose if you'd like to keep all data from both tables in your result set, or if you prefer to keep only matching records.
Tableau is a great tool for operationalizing time period comparisons. One of the classics is comparing quarters.
For example, you might want to know how this quarter compares to last quarter. That's a great way to compare values if your business isn't very seasonal. However, what if you sell sunscreen? You can bet that comparing fall to summer is always going to look like a bummer.
When it comes to displaying data over time, it's easy to fall into the trap that you should always use some form of line graph. While line graphs are a great default when displaying chronological data, they aren't always your best option!
Aggregations are functions which allow you to consolidate numerous rows of values into a single output. SUM, AVG, MIN, MAX, COUNT and COUNTD are some of the most used aggregations in Tableau.
Aggregations play an important role in Tableau calculations. If they aren't used properly, calculations will return incorrect results!
A huge benefit of using joins in Tableau is that we can combine data from multiple tables into a single table for analysis. When those tables are in different databases, it can be a little tricky to work out where to start. If you know how to join tables within the same database, that's great! Cross-database joins only take a few more steps to execute, and I'll walk you through them in today's video.
Every application seems to have it's own syntax for IF logic statements, right? SQL, Excel and Tableau IF statements all look a little different.
Check this video out for a deep dive into the world of logical operators, simple and advanced IF statements in Tableau!
If you are coming to Tableau from the world of Excel, make sure your skills translate!
Excel and Tableau have a long history of being complementary tools. While there are functions that can be performed in both tools, they both have their own strengths and weaknesses.
Do you want to keep all data associated with a value which has multiple records in a data set? Maybe it's how many students attended multiple schools, how many patients visited a hospital multiple times or how many customers made multiple purchases.
