Tableau on tour - reaches London

Ok, here is my attempt at live blogging so this page will capture my thoughts and key ideas throughout the conference (if the wifi holds up).

Opening keynote:
- 7,000 people expected in Seattle for the global conference this year. Should be epic!

- A great demonstration of Tableau Public through Paul Banoub's cup stacking viz

- Francois Ajenstat giving really good insights into the founding of Tableau. Chris, Christian and Pat had to produce multiple visualisation to describe some code - they desired to find an easy way to do this.

- Key areas for development for tableau:
1. Seamless access to data - new data load in 8.2 a key part of this
2. Analytics and statistics for everyone - sophisticated modelling in one click. Mapping the big development in 8.2. Data search to be developed in future releases.
3. Visual Analytics everywhere - Dave Story - former Lucas Films BI guru, now mobile and strategic growth VP highlights edit function on server to explore further through 'edit' functionality.
4. Storytelling - Powerpoint just isn't enough anymore! Check out my Viz of the Day in the article below to see more.
5. Enterprise - Tableau. Online and Public shows scalability. New administration functions in 8.2 to add, edit and delete users / workbooks the latest iteration.
6. Fast, easy, beautiful - Tableau want you to have a "conversation with the data so the software fades away". Subtle changes like responsive marks on maps, seamless movement around maps etc

Paul Banoub's talk on building a Tableau Centre of Excellence
- UBS using Tableau for IT, Business, Finance and HR

- It's not just about Tableau it's about Visualisation best practice.

- Design for Homer as well as Lisa Simpson - don't just build shareable work for people like you. It won't have the same benefit if not.

- Proof of concepts and communities are key ways to find who gets hooked on Tableau. Similar experience for me too apart from people who see Tableau over your shoulder and go "I want to do that"

- Virtual Hosting, Monitoring (great work by Mike Roberts formerly of Interworks that I will need to read after), Configuration all need to be considered to create the polished user experience that Tableau is designed for. Landing pages on intranet and style guides help users to get better results sooner (ref. Mark Jackson's blog ugamarkj.blogspot.com)

- Purchaisng and onboarding new users is cruical to the user experience. It can really put people off Tableau if you falter and are not timely. *nods*

- Monthly and Quarterly structured training sessions (including Tableau doctor sessions) have helped people excel and drive themselves further.

Bethany Lyons - data blending
- Data blending is a left outer join (everything from left (primary) and brings in just the stuff that matches in the right (secondary)). Inner joins are also possible by excluding any nulls. Can't do full outer joins through blends.

- Try to aggregate through linking fields for better performance. These will be the most common request anyway.

- The combination of highlighted link icons will create the unique combination of data points to be joined. Over selection of data links leads to data reduction (data points disappearing) if you just select everything but are actually not concerned about that unique combination of data points. - To prevent data loss then you need to pad the domain - this means adding null values to ensure there is a cross over between both data sets on all of the linking fields

- * value of doom (hopefully will be called the Death Star) - occurs when your secondary data source has a many-to-one relationship with the primary data source. This doesn't happen with joins as joins create additional rows of data but likely will duplicate the measure value.

- If you want to filter between two data sources, joins are the way to go. Because when one set is used as a filter but it has no concept of that filter in the second data source, Tableau can't filter it. - You could then join these two source abut blend in the measures to avoid duplication of values.

Jock McKinley
- Story arc - Question or problem, Logical sequence or narrative, and Conclusion or Resolution

- Three types of use of visualisation in storytelling - 1. Find, 2. Tell and 3. Explore

- Tell - Jock used a great connected Scatterplot on road fatalities in motor vehicles by Hannah Fairfield. Chart run through the story and annotation is all around. Body of text in large dead white space. Very much a tell style.

- Use "Information Scent" (highlight function in Tableau) to lead others to explore your data.

- Explore - people don't expect data views to be a place to explore. You need to show them you can and how. D3 line charts used heavily in good examples. Allows people to explore.

- Collaborate - share and you never know where someone will take your data and story too.

- This will truly create a tree of knowledge

Andy Kriebel and Dan Murray
- Dan - "Andy is the smartest dumb guy you'll ever meet" nice!

- 1st user meeting was 2009 in Atlanta, Andy Cotgrave created the 1st User Group in the UK in 2010 (a contentious point!)

- 10. Rules of running a good user group:
1. Multiple companies and leaders mean that there is a good supply of organisers and spaces to choose from
2. Make it a no sales zone - listen to what the users want
3. Make it routine - monthly or quarterly so people can get it in to their diaries
4. Central location, easy accessibility key to remove excuses not to attend
5. Webinar make it tough as you don't really get to meet people. Allow webex, but just don't promote it
6. Andy - "beer helps"
7. 3-4 hours is key duration time
8. What? Guest speaker (can be wider than Tabelau), hands on training (helps newbies, don't go too advanced), give a random data set and allow people to build.
9. You want people to get hooked to come back so the takeaway learnings need to be good
10. Always have the next meeting ready to go...

Bethany Lyons - Table Calculations
- All the major work is done within advanced settings of the table calc. Using this rather than the drop downs mean that as you change the visualisation, the table calculation will remain calculating what you want by what you want

- Difference from average - sum(sales)-window_avg(sum(sales))

- You can nest as many table calculations as you want. You'd be crazy or a zen master to do this but you could

- dayofyear - is a number of the day in the year and is used within date part calculation syntax (I've never come across it)

- Last() is the table calculation that I always forget about but saves working on date calculations

- ATTR is a way to aggregate dimensions to be used within table calcs where you are using aggregated measures

- Jittering in a box-plot - use index() and change the partition to be your dimension