Additional resources:
• Tableau Starter Kits https://www.tableau.com/learn/starter-kits
• Free How-To Training Videos https://www.tableau.com/learn/training
• Tableau Product Support https://www.tableau.com/support
• Tableau Product Help https://www.tableau.com/support/help
- Tableau desktop online help https://onlinehelp.tableau.com/current/pro/desktop/en-us/default.htm
- Visual Best Practices https://www.tableau.com/learn/whitepapers/tableau-visual-guidebook?signin=c6cf87638b3864d1c393ffafb79ae10c
Tableau Certificate Exam Learning Resources
- Learning Tableau Notes
- Tableau Qualified Associated Exam https://www.linkedin.com/pulse/i-got-tableau-certified-you-can-too-saahithi-jyothy-surapaneni/
- https://biztory.com/2017/02/17/ace-tableau-desktop-qualified-associate-exam/
- Tableau Qualified Associate Certification Quizzes https://learningtableau.com/
- Equations of Trend Line: https://www.khanacademy.org/math/probability/scatterplots-a1/estimating-trend-lines/a/equations-of-trend-lines-phone-data
- The slope of the trend line represents the predicted change in the vertical variable that's associated with a one-unit change in the horizontal variable.
- e.g. y = −0.75x + 9, x, time spent on phone, y, battery life remaining. For each additional 1 hour of time spent on the phone, the predicted battery life remaining decreases by 0.75 hours.
- The y-intercept of the model describes the predicted y value when x = 0.
- When the time spent on her phone is 0 hours, the predicted battery life remaining is 9 hours.
- Use the trend line to predict the battery life remaining after 20 hours of phone use. The predicted battery life is -6 hours.
- The slope of the trend line represents the predicted change in the vertical variable that's associated with a one-unit change in the horizontal variable.
- LOD
- top 15 LOD expressions https://www.tableau.com/about/blog/LOD-expressions
How Level of Detail Expressions Work in Tableau https://onlinehelp.tableau.com/current/pro/desktop/en-us/calculations_calculatedfields_lod_overview.htm
For example, if you attempt to save the following expression, Tableau displays the error message: “Cannot mix aggregate and non-aggregate arguments with this function”:
[Sales] – AVG([Sales]). In this expression, [Sales] is a row level expression, whereas AVG([Sales]) is an aggregate function.
The user’s intent in this case was to compare store sales for each individual store to the average of sales for all stores. This can now be accomplished with a level of detail expression:
[Sales] - {AVG([Sales])}. So the Table-scoped LOD is a row level expression.
This is what is known as a table-scoped level of detail expression. See Table-Scoped.
Table-Scoped
It is possible to define a level of detail expression at the table level without using any of the scoping keywords. For example, the following expression returns the minimum (earliest) order date for the entire table:{MIN([Order Date])}
This is equivalent to a FIXED level of detail expression with no dimension declaration:
{FIXED : MIN([Order Date])}
Standard deviation 5 built-in stats functions you didn’t know Tableau had
Read more at https://www.tableau.com/about/blog/2017/5/5-built-stats-functions-you-didnt-know-tableau-had-71047#Ie7YC370KgmItK3q.99Q&A
Which type of connection support Extract ? Select all that apply (all four choices)
1. Join
2. Blend
2. Cross Database Join
4. Union
- Which file type supports live connection https://onlinehelp.tableau.com/current/pro/desktop/en-us/exampleconnections_overview.htm supported conectors
- Microsoft Excel
- text file (delimited text files (*.txt, *.csv, *.tab, *.tsv)
- JSON
- PDF