from Tableau 201
 
First, holy cow! What an awesome resource Ryan has put together!! 
Shaping data

• It's optimal to have one column representing one field (layout is vertical not horizontal)
• One recommendation for time: if it's presented as 1Q16, add a column to data for the actual date (3/31/16) 

Measures vs Dimensions

• Measure is quantitative and dependent (i.e Sales by itself just gives you a total but a  dimension will give it context (sales by region) 
• General rule of thumb: measure is a number, dimension is what to slice & dice by
• A good question to ask when you have numbers as data items, does it make sense to sum it up? If yes, then measure. If no, then it's likely a dimension. 
• When null is the first value, Tableau may misclassify because the first value is a string. 

Discrete vs Continuous 

• Discrete is blue, continuous is green pill (Emma Whyte would smack me for using the incorrect term of pill).
• Discrete fields draw headers (which can be sorted) while continuous draw axes (cannot be sorted).

Level of Detail for a View

• The detail marks card allows you add a dimension which can take a view from a high level of aggregation to be more granular (defined by that dimension). 
  • It's not the only way but another way that may help the viz process flow better. 

I have been wanting to focus on building my technical skills for awhile now. I go in fits and starts but I know that I need to be consistent so I can can capitalize on my learnings. My challenge: limited time given my work, my mom status, & my fitness which is just as, if not more, important to me. So, I'm developing a plan with the help of a few friends to help me stay on track.

The Plan
To balance my life, I'm planning to spend three-five hours per week on data viz. it's not a lot compared to what others might spend, but I think it's realistic for me (and that's what's important).
Review trainings available such as

• Ryan Sleeper's Tableau 201
• Review the Qualified Associates test materials
• www.learntableau.com
• Finish reading Ben Jones's Communicating Data with Tableau
• Read Andy Kirk's book, Data Visualisation: A Handbook for Data Driven Design
  

Practical Application

• Weekly viz, typically focusing on a certain training aspect
• Monthly viz

​Document Learnings
Each week, I'll recap my notes in a basic blogpost which will range from good reminders I want to remember to new concepts I've learned.

While this is my personal study notebook, I hope others might also find it useful!

Now, time to hit the books!

From Tableau 201

First, holy cow! What an awesome resource Ryan has put together!!

Shaping data

• It's optimal to have one column representing one field (layout is vertical not horizontal)
• One recommendation for time: if it's presented as 1Q16, add a column to data for the actual date (3/31/16)

Measures vs Dimensions

• Measure is quantitative and dependent (i.e Sales by itself just gives you a total but a dimension will give it context (sales by region)

• General rule of thumb: measure is a number, dimension is what to slice & dice by
• A good question to ask when you have numbers as data items, does it make sense to sum it up? If yes, then measure. If no, then it's likely a dimension.
• When null is the first value, Tableau may misclassify because the first value is a string.

Discrete vs Continuous

• Discrete is blue, continuous is green pill (Emma Whyte would smack me for using the incorrect term of pill).
• Discrete fields draw headers (which can be sorted) while continuous draw axes (cannot be sorted).

Level of Detail for a View

• The detail marks card allows you add a dimension which can take a view from a high level of aggregation to be more granular (defined by that dimension).

• It's not the only way but another way that may help the viz process flow better. 

​I have been wanting to focus on building my technical skills for awhile now. I go in fits and starts but I know that I need to be consistent so I can can capitalize on my learnings. My challenge is the limited time I have given my work status, mom status, & my fitness which is just as, if not more, important to me. So, I'm developing a plan with the help of a few friends to help me stay on track.

The Plan

To balance my life, I'm planning to spend three-five hours per week on data viz. it's not a lot compared to what others might spend, but I think it's realistic for me (and that's important).

Review training available such as

• Ryan Sleeper's Tableau 201
• Review the Qualified Associates test materials
• www.learntableau.com
• Finish reading Ben Jones's Communicating Data with Tableau
• Read Andy Kirk's book, Data Visualization: A Handbook for Data Driven Design

Practical Application

• Weekly viz, typically focusing on a certain training aspect
• Monthly viz

Document Learning

Each week, I'll recap my notes in a basic blogpost which will range from good reminders I want to remember to new concepts I've learned.

While this is my personal study notebook, I hope others might also find it useful!

Now, time to hit the books! 

It's that magical time of year when Tableau opens up Zen Master nominations. What are the criteria? Check out the image below which I snapped from Tableau.

I'm encouraging everyone to nominate folks. The deciders may not know how awesome someone is unless they see the nomination. I've got three tips that I wanted to share when nominating someone. This is my advice/opinion only (not Tableau's).

Is there some other relevant consideration that you think should be included? I say, add it. I *think* it helps the deciders have sufficient, relevant information. Only think the person meets three of four questions, but rocks the F out of those three? Make the case.

Use data (whaaaaaatt!!). Provide evidence that the person you are nominating has demonstrated their zen-ness. Blog all the time? Tell them. Present all the time? Provide links. I think you get the idea.

This one is actually just a pet peeve of mine. Make sure your message is not distracted by poor spelling and grammar.

Now, my biggest piece of advice!

One reason why I hosts events like The Vizzies or the Tableau Fringe Festival is that we have a kickass community and I want to highlight the people in it. Zens have a platform others don't (Zens on Tour, the Zen track at conference). All of the really awesome folks can't be Zen Masters. And that's okay. Being a Zen Master doesn't mean you are the best person. Some Zen Masters demonstrate better leadership qualities than others. It doesn't define how nice you are, whether you are smart, a good family member, or a fantastic data storyteller. So for all the people out there who are hoping to attain or retain their Zen Master status, my message to you is this:

If you want to be a Zen Master and you've demonstrated those qualities, I hope you get it. But if you don't, don't fret.